From ce27dca65c072ce72ae021517dac19c6326e43f3 Mon Sep 17 00:00:00 2001 From: Gokhan Date: Wed, 8 Dec 2021 01:13:44 +0100 Subject: [PATCH] add: new functions, gui --- README.md | 25 +- ...enna-60Noise-3x3-BVDF-VMF-DDF-alsoDiff.fig | Bin 0 -> 1236525 bytes ...enna-60Noise-3x3-BVDF-VMF-DDF-alsoDiff.pdf | Bin 0 -> 944585 bytes results/Lenna-VMF-BVDF-60.pdf | Bin 0 -> 956942 bytes .../{bvdf_plot_vectors.m => 3DVectorPlot.m} | 6 +- .../{bvdf_add_noise.m => AddPseudoNoise.m} | 4 +- src/API/{bvdf_present.m => BVDF_Present.m} | 0 ...ilter.m => BasicVectorDirectionalFilter.m} | 4 +- src/API/ColorImageDifference.m | 25 + src/API/DistanceDirectionalFilter.m | 73 ++ ...df_sort_vectors.m => SortVectorsbyAngle.m} | 2 +- src/API/VMF_BVDF_Present.m | 29 + src/API/VectofilPlus.prj | 135 +++ src/API/VectorMedianFilter.m | 50 + src/GUI/vectofil.mlapp | Bin 83416 -> 88847 bytes src/GUI/vectofil_plus.m | 964 ++++++++++++++++++ 16 files changed, 1301 insertions(+), 16 deletions(-) create mode 100644 results/Lenna-60Noise-3x3-BVDF-VMF-DDF-alsoDiff.fig create mode 100644 results/Lenna-60Noise-3x3-BVDF-VMF-DDF-alsoDiff.pdf create mode 100644 results/Lenna-VMF-BVDF-60.pdf rename src/API/{bvdf_plot_vectors.m => 3DVectorPlot.m} (88%) rename src/API/{bvdf_add_noise.m => AddPseudoNoise.m} (94%) rename src/API/{bvdf_present.m => BVDF_Present.m} (100%) rename src/API/{bvdf_filter.m => BasicVectorDirectionalFilter.m} (89%) create mode 100644 src/API/ColorImageDifference.m create mode 100644 src/API/DistanceDirectionalFilter.m rename src/API/{bvdf_sort_vectors.m => SortVectorsbyAngle.m} (95%) create mode 100644 src/API/VMF_BVDF_Present.m create mode 100644 src/API/VectofilPlus.prj create mode 100644 src/API/VectorMedianFilter.m create mode 100644 src/GUI/vectofil_plus.m diff --git a/README.md b/README.md index 53df5d3..860e3d7 100644 --- a/README.md +++ b/README.md @@ -1,15 +1,24 @@ # vectofil+ -A program to perform Basic Vector Directional Filtering for the noisy color images. This a project of Computer Vision and Image Processing course in West Pomeranian University of Technology. +A program to perform Basic Vector Directional Filtering for the noisy colour images. This a project of Computer Vision and Image Processing course in West Pomeranian University of Technology. -For the demostration, check out Results directory, or [see the GUI on YouTube](https://www.youtube.com/watch?v=pXBCrB0VlLY). +For the demonstration, check out Results directory, or [see the GUI on YouTube](https://www.youtube.com/watch?v=pXBCrB0VlLY). ### What we will add? -- Save the output functionality. -- Save the process as a PDF and PNGs functionality -- Choosing the Vector Median Filtering or Basic Vector Directional Filtering process. Comperasion between two filters. -- Percentage addition between VMF and BVDF. -- Much more pretty UI! -- Documentation for every function. Especially lots of comments on the file of BVDF_FILTER. + +- [ ] Save the output functionality. + +- [ ] Save the process as a PDF and PNGs functionality. + +- [x] Choosing the Vector Median Filtering or Basic Vector Directional Filtering process. Comperasion between two filters. + +- [x] Percentage addition between VMF and BVDF. + +- [x] Much more pretty UI! + +- [ ] Documentation for every function. Especially lots of comments on the file of BVDF_FILTER. ### License This is a art of open source. 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src/API/bvdf_plot_vectors.m rename to src/API/3DVectorPlot.m index 50efa74..6349a1b 100644 --- a/src/API/bvdf_plot_vectors.m +++ b/src/API/3DVectorPlot.m @@ -1,5 +1,5 @@ -function bvdf_plot_vectors(vectors, origin, ColorScheme) -% BVDF_PLOT_VECTORS The function plots the 3D vectors in space. +function 3DVectorPlot(vectors, origin, ColorScheme) +% 3DVectorPlot The function plots the 3D vectors in space. % Only and first parameter is the matrix which every column is a vector. % Control if the optional arguments are given. @@ -34,4 +34,4 @@ function bvdf_plot_vectors(vectors, origin, ColorScheme) end hold off; -end \ No newline at end of file +end diff --git a/src/API/bvdf_add_noise.m b/src/API/AddPseudoNoise.m similarity index 94% rename from src/API/bvdf_add_noise.m rename to src/API/AddPseudoNoise.m index 59dddb4..0af75ed 100644 --- a/src/API/bvdf_add_noise.m +++ b/src/API/AddPseudoNoise.m @@ -1,4 +1,4 @@ -function noisy_img = bvdf_add_noise(image, perc, channel_size, assigned) +function noisy_img = AddPseudoNoise(image, perc, channel_size, assigned) noisy_img = image; % Travel throught every pixel. @@ -27,4 +27,4 @@ end end end -end \ No newline at end of file +end diff --git a/src/API/bvdf_present.m b/src/API/BVDF_Present.m similarity index 100% rename from src/API/bvdf_present.m rename to src/API/BVDF_Present.m diff --git a/src/API/bvdf_filter.m b/src/API/BasicVectorDirectionalFilter.m similarity index 89% rename from src/API/bvdf_filter.m rename to src/API/BasicVectorDirectionalFilter.m index 022a669..643bee7 100644 --- a/src/API/bvdf_filter.m +++ b/src/API/BasicVectorDirectionalFilter.m @@ -1,4 +1,4 @@ -function filtered_image = bvdf_filter(image, sample_dims) +function filtered_image = BasicVectorDirectionalFilter(image, sample_dims) % BVDF_FILTER Function to filter the image according the BVDF rule. if nargin < 2 error("You have to give the image as uint8 matrix, and dimensions of the vectoral process."); @@ -21,7 +21,7 @@ area2filter = im2double(area2filter).*255; vectors_list = reshape(area2filter , [], 3)'; - sorted_vectors = bvdf_sort_vectors(vectors_list); + sorted_vectors = SortVectorsbyAngle(vectors_list); filtered_image(x_index, y_index, :) = sorted_vectors(:, 1); end end diff --git a/src/API/ColorImageDifference.m b/src/API/ColorImageDifference.m new file mode 100644 index 0000000..ea15b0f --- /dev/null +++ b/src/API/ColorImageDifference.m @@ -0,0 +1,25 @@ +% COLORIMAGEDIFFERENCE + +function [resultedImage, differentPixelCount] = ColorImageDifference(image1, image2) + sizeImg1 = size(image1); + sizeImg2 = size(image2); + differentPixelCount = 0; + + if (sizeImg1 - sizeImg2) ~= zeros(1, 3) + error("Given input images' sizes are not matched."); + end + + resultedImage = zeros(sizeImg1); + + for rowPixel = 1:sizeImg1(1) + for colPixel = 1:sizeImg1(2) + if min(... + image1(rowPixel, colPixel, :) == image2(rowPixel, colPixel, :)... + ) == 0 + + resultedImage(rowPixel, colPixel, :) = [255, 255, 255]'; + differentPixelCount = differentPixelCount + 1; + end + end + end +end \ No newline at end of file diff --git a/src/API/DistanceDirectionalFilter.m b/src/API/DistanceDirectionalFilter.m new file mode 100644 index 0000000..24b13e7 --- /dev/null +++ b/src/API/DistanceDirectionalFilter.m @@ -0,0 +1,73 @@ +function filtered_image = DistanceDirectionalFilter(corrupted_image, window_size, BVDFratio, yValueVMF) + image_X = size(corrupted_image, 1); + image_Y = size(corrupted_image, 2); + + filtered_image = zeros(size(corrupted_image)); + starting_points = [ceil(window_size/2), ceil(window_size/2)]; + choosing_distance = [floor(window_size/2), floor(window_size/2)]; + + for x_index = starting_points(1):(image_X-starting_points(1)) + for y_index = starting_points(2):(image_Y-starting_points(2)) + + area2filter = corrupted_image(x_index-choosing_distance(1):x_index+choosing_distance(2),... + y_index-choosing_distance(2):y_index+choosing_distance(2), :); + area2filter = im2double(area2filter).*255; + vectors_list = reshape(area2filter , [], 3)'; + + % Sorting Process + % In here, one array of vectors is created. First row will give + % us the distances calculated with VMF, second row will give us + % the angles calculated with BVDF. That's why there is "+2". + calculations = zeros(size(vectors_list, 1) + 3, size(vectors_list, 2)); + calculations(4:end, :) = vectors_list; + + for index = 1:size(vectors_list, 2) + for jndex = 1:size(vectors_list, 2) + + % For each pixel, we are choosing the window-size of + % pixels, and calculate the angles and distances from + % them. + + vectA = vectors_list(:, index); + vectB = vectors_list(:, jndex); + + if vectA == vectB + continue; + end + + % BVDF method for window-sized vectors. + calculations(3, index) = calculations(2, index) + ... + acosd(dot(vectA, vectB) / (norm(vectA) * norm(vectB))); + + % VMF method for window-sized vectors with Euclodien distances. + colorRed = (vectA(1) - vectB(1)).^(yValueVMF); + colorGreen = (vectA(2) - vectB(2)).^(yValueVMF); + colorBlue = (vectA(3) - vectB(3)).^(yValueVMF); + VMF_distance = (colorRed + colorGreen + colorBlue).^(1/yValueVMF); + calculations(2, index) = calculations(2, index) + VMF_distance; + + end + end + + % Combination of VMF and BVDF: Distance Directional Filter + calculations(1, :) = (calculations(3, :).^(BVDFratio)) .* (calculations(2, :).^(1-BVDFratio)); + + % Sorting the vectors inside the window, with the rules of BVDF + % and VMF. + % [~, VMForder] = sort(calculations(2, :)); + % [~, BVDForder] = sort(calculations(3, :)); + % VMFSortedVects = calculations(3:end, VMForder); + % BVDFSortedVects = calculations(3:end, BVDForder); + % VMF_Vector = VMFSortedVects(:, 1); + % BVDF_Vector = BVDFSortedVects(:, 1); + [~, DDForder] = sort(calculations(1, :)); + DDFSortedVects = calculations(4:end, DDForder); + DDF_Vector = DDFSortedVects(:, 1); + + filtered_image(x_index, y_index, :) = DDF_Vector; + + end + end + + filtered_image = cast(filtered_image, 'uint8'); +end \ No newline at end of file diff --git a/src/API/bvdf_sort_vectors.m b/src/API/SortVectorsbyAngle.m similarity index 95% rename from src/API/bvdf_sort_vectors.m rename to src/API/SortVectorsbyAngle.m index baf7d14..5477d55 100644 --- a/src/API/bvdf_sort_vectors.m +++ b/src/API/SortVectorsbyAngle.m @@ -1,4 +1,4 @@ -function [sorted_vectors, sorted_angles] = bvdf_sort_vectors(vectors) +function [sorted_vectors, sorted_angles] = SortVectorsbyAngle(vectors) % BVDF_VECTOR_SORT A function to sort the given n-dimensional vectors. % Parameter vectors has to be a matrix which every column represents a % vector. Function returns a vector, first element is the sorted vectors' diff --git a/src/API/VMF_BVDF_Present.m b/src/API/VMF_BVDF_Present.m new file mode 100644 index 0000000..3a2cf8a --- /dev/null +++ b/src/API/VMF_BVDF_Present.m @@ -0,0 +1,29 @@ +function VMF_BVDF_Present(corrupted_image) + vmf_result = VectorMedianFilter(corrupted_image, 3); + bvdf_result = bvdf_filter(corrupted_image, 3); + [diff_img, diff_img_count] = ColorImageDifference(vmf_result, bvdf_result); + hybrid_result = VMF_BVDF_Combine(corrupted_image, 3); + + SameRatio = (size(corrupted_image, 1) .* size(corrupted_image, 2) - diff_img_count) ... + / (size(corrupted_image, 1) .* size(corrupted_image, 2)); + sprintf("Sameness Ratio: %d", SameRatio); + + tiledlayout(2,3) + nexttile + imshow(corrupted_image) + title("Corrupted Image") + nexttile + imshow(vmf_result) + title("VMF") + nexttile + imshow(bvdf_result) + title("BVDF") + nexttile + imshow(diff_img) + title("Img Diff") + nexttile + imshow(hybrid_result) + title("Hybrid") + + +end \ No newline at end of file diff --git a/src/API/VectofilPlus.prj b/src/API/VectofilPlus.prj new file mode 100644 index 0000000..69e4c24 --- /dev/null +++ b/src/API/VectofilPlus.prj @@ -0,0 +1,135 @@ + + + VectofilPlus + + + 1.0 + Gökhan Koçmarlı + gokhankocmarli@gmail.com + West Pomeranian University of Technology + A GUI based application to create noise, and filter color images with Basic Vector Directional Filters. + + + + /VectofilPlus/ + option.installpath.user + + + In the following directions, replace MR/v910 by the directory on the target machine where MATLAB is installed, or MR by the directory where the MATLAB Runtime is installed. + +(1) Set the environment variable XAPPLRESDIR to this value: + +MR/v910/X11/app-defaults + + +(2) If the environment variable LD_LIBRARY_PATH is undefined, set it to the following: + +MR/v910/runtime/glnxa64:MR/v910/bin/glnxa64:MR/v910/sys/os/glnxa64:MR/v910/sys/opengl/lib/glnxa64 + +If it is defined, set it to the following: + +${LD_LIBRARY_PATH}:MR/v910/runtime/glnxa64:MR/v910/bin/glnxa64:MR/v910/sys/os/glnxa64:MR/v910/sys/opengl/lib/glnxa64 + ${PROJECT_ROOT}/VectofilPlus/for_testing + ${PROJECT_ROOT}/VectofilPlus/for_redistribution_files_only + ${PROJECT_ROOT}/VectofilPlus/for_redistribution + ${PROJECT_ROOT}/VectofilPlus + false + + subtarget.standalone + + true + false + false + MyAppInstaller_web + MyAppInstaller_mcr + MyAppInstaller_app + false + false + + false + false + + Syntax + -? + + Input Arguments + -? print help on how to use the application + input arguments + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ${PROJECT_ROOT}/GUI/vectofil.mlapp + + + + + + /media/pop49/Data/Projeler/Dersler/West Pomaranian University of Technology/Computer Vision and Image Processing/Basic Vector Directional Filters/VectofilPlus/for_testing/run_VectofilPlus.sh + /media/pop49/Data/Projeler/Dersler/West Pomaranian University of Technology/Computer Vision and Image Processing/Basic Vector Directional Filters/VectofilPlus/for_testing/VectofilPlus + /media/pop49/Data/Projeler/Dersler/West Pomaranian University of Technology/Computer Vision and Image Processing/Basic Vector Directional Filters/VectofilPlus/for_testing/splash.png + /media/pop49/Data/Projeler/Dersler/West Pomaranian University of Technology/Computer Vision and Image Processing/Basic Vector Directional Filters/VectofilPlus/for_testing/readme.txt + + + + /media/pop49/LinuxApps/MATLABR2021A + + + + + + + true + + + + + true + + + + + true + false + false + false + false + false + true + false + 5.11.0-7620-generic + false + true + glnxa64 + true + + + \ No newline at end of file diff --git a/src/API/VectorMedianFilter.m b/src/API/VectorMedianFilter.m new file mode 100644 index 0000000..6be0ba1 --- /dev/null +++ b/src/API/VectorMedianFilter.m @@ -0,0 +1,50 @@ +function filtered_image = VectorMedianFilter(image, window_size) + image_X = size(image, 1); + image_Y = size(image, 2); + + filtered_image = zeros(size(image)); + starting_points = [ceil(window_size/2), ceil(window_size/2)]; + choosing_distance = [floor(window_size/2), floor(window_size/2)]; + + for x_index = starting_points(1):1:(image_X-starting_points(1)) + for y_index = starting_points(2):1:(image_Y-starting_points(2)) + + area2filter = image(x_index-choosing_distance(1):x_index+choosing_distance(2),... + y_index-choosing_distance(2):y_index+choosing_distance(2), :); + area2filter = im2double(area2filter).*255; + vectors_list = reshape(area2filter , [], 3)'; + + % SORTING + distances = zeros(size(vectors_list, 1) + 1, size(vectors_list, 2)); + distances(2:end, :) = vectors_list; + + for index = 1:size(vectors_list, 2) + for jndex = 1:size(vectors_list, 2) + + vectA = vectors_list(:, index); + vectB = vectors_list(:, jndex); + + if vectA == vectB + continue; + end + + % No need for abs() function, because it'll be + % rised by 2. + dist_r = vectA(1) - vectB(1); + dist_g = vectA(2) - vectB(2); + dist_b = vectA(3) - vectB(3); + euclidean_dist = floor(sqrt(dist_r^2 + dist_g^2 + dist_b^2)); + + distances(1, index) = distances(1, index) + euclidean_dist; + end + end + + [~, order] = sort(distances(1, :)); + sorted_vectors = distances(2:end, order); + filtered_image(x_index, y_index, :) = sorted_vectors(:, 1); + + end + end + + filtered_image = cast(filtered_image, 'uint8'); +end \ No newline at end of file diff --git a/src/GUI/vectofil.mlapp b/src/GUI/vectofil.mlapp index b6e0dc131abc1b89f969fd0463cbd65d03b16452..ca011e252befbb03310b84b8af1e8f47f9be8b9f 100644 GIT binary patch delta 87114 zcmV(xKc5ZAe#UHoSTzes~>;4Wl)?=(*{a{ z1&81cK^6-n=(0G30098q#js-Bq|MG18U2}wFW&JT2o66){GEv?Ns=#;I$Ihor!`~=a-D1fyk_<1?#q#Vq? zIhmQ#+1h~Uv|jipGZTM0Iw0MLkDw2NAZ{QX_XqBebpJn_HyzUd+ABFlycg#3LT=Cv zldoUhUUgfG554MEz{YRK+~Rrnjgt;MGWx!MRDPJ9HKfSo+iK82;I6V#{m{jDwtC@5 zY%lRef74bvbtnP2`oj(A9zF2pwKz0QI}VbZtCd=W{t-QQ1zCSij4SniHfFI8X-i%_ z*)`?gA{S0KlA_>SuK&<)Y5qfp>FC)`$P(d}RF$FxBs7T7#pcy_T5Bes75^ 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% Check condition if its in interval for assign noise. + if (min((interval(:, 1) < reshaped_area)) && ... + min(reshaped_area < interval(:, 2))) + app.NoisyImage(index, jndex, :) = app.NoiseColour; + end + end + end + + app.NoisyImageCanvas.ImageSource = app.NoisyImage; + end + + function [sorted_vectors, sorted_angles] = SortVectorsbyAngle(~, vectors) + % BVDF_VECTOR_SORT A function to sort the given n-dimensional vectors. + % Parameter vectors has to be a matrix which every column represents a + % vector. Function returns a vector, first element is the sorted vectors' + % matrix, and the second element is the sorted angles. + + % Create a zero-matrix for results, and assign our vectors into. First + % row for the angles, and the remaining rows for the vectors. I'm + % making this way, because sorting function works only this way. + angles = zeros(size(vectors, 1) + 1, size(vectors, 2)); + angles(2:end, :) = vectors; + + % Choose the reference point for calculation. + for index = 1:size(vectors, 2) + % Travel every element to find angle according to reference element. + for jndex = 1:size(vectors, 2) + + vectorA = vectors(:, index); + vectorB = vectors(:, jndex); + + % If it's the same element, do not calculate angle because it's + % zero. + if vectorA == vectorB + continue; + end + + % Add the indexth elements' angle for each element angle. + angles(1, index) = angles(1, index) + acosd(dot(vectorA, vectorB) / (norm(vectorA) * norm(vectorB))); + end + end + + % Sort process according the first row. + [sorted_angles, order] = sort(angles(1, :)); + sorted_vectors = angles(2:end, order); + end + + function filtered_image = BasicVectorDirectionalFilter(app, image, window_size) + % BVDF_FILTER Function to filter the image according the BVDF rule. + if nargin < 2 + error("You have to give the image as uint8 matrix, and dimensions of the vectoral process."); + end + + color_count = size(image, 3); + image_X = size(image, 1); + image_Y = size(image, 2); + + starting_points = [ceil(window_size/2), ceil(window_size/2)]; + choosing_distance = [floor(window_size/2), floor(window_size/2)]; + filtered_image = zeros(image_X, image_Y, color_count); + + for x_index = starting_points(1):1:(image_X-starting_points(1)) + for y_index = starting_points(2):1:(image_Y-starting_points(2)) + + area2filter = image(x_index-choosing_distance(1):x_index+choosing_distance(2),... + y_index-choosing_distance(2):y_index+choosing_distance(2), :); + + area2filter = im2double(area2filter).*255; + + vectors_list = reshape(area2filter , [], 3)'; + sorted_vectors = app.SortVectorsbyAngle(vectors_list); + filtered_image(x_index, y_index, :) = sorted_vectors(:, 1); + end + end + + filtered_image = cast(filtered_image, 'uint8'); + + end + + function filtered_image = VectorMedianFilter(app, image, window_size) + image_X = size(image, 1); + image_Y = size(image, 2); + + filtered_image = zeros(size(image)); + starting_points = [ceil(window_size/2), ceil(window_size/2)]; + choosing_distance = [floor(window_size/2), floor(window_size/2)]; + + for x_index = starting_points(1):1:(image_X-starting_points(1)) + for y_index = starting_points(2):1:(image_Y-starting_points(2)) + + area2filter = image(x_index-choosing_distance(1):x_index+choosing_distance(2),... + y_index-choosing_distance(2):y_index+choosing_distance(2), :); + area2filter = im2double(area2filter).*255; + vectors_list = reshape(area2filter , [], 3)'; + + % SORTING + distances = zeros(size(vectors_list, 1) + 1, size(vectors_list, 2)); + distances(2:end, :) = vectors_list; + + for index = 1:size(vectors_list, 2) + for jndex = 1:size(vectors_list, 2) + + vectA = vectors_list(:, index); + vectB = vectors_list(:, jndex); + + if vectA == vectB + continue; + end + + % No need for abs() function, because it'll be + % rised by 2. + dist_r = vectA(1) - vectB(1); + dist_g = vectA(2) - vectB(2); + dist_b = vectA(3) - vectB(3); + euclidean_dist = floor(sqrt(dist_r^2 + dist_g^2 + dist_b^2)); + + distances(1, index) = distances(1, index) + euclidean_dist; + end + end + + [~, order] = sort(distances(1, :)); + sorted_vectors = distances(2:end, order); + filtered_image(x_index, y_index, :) = sorted_vectors(:, 1); + + end + end + + filtered_image = cast(filtered_image, 'uint8'); + + + end + + + function filtered_image = DistanceDirectionalFilter(app, corrupted_image, window_size, BVDFratio, yValueVMF) + image_X = size(corrupted_image, 1); + image_Y = size(corrupted_image, 2); + + filtered_image = zeros(size(corrupted_image)); + starting_points = [ceil(window_size/2), ceil(window_size/2)]; + choosing_distance = [floor(window_size/2), floor(window_size/2)]; + + for x_index = starting_points(1):(image_X-starting_points(1)) + for y_index = starting_points(2):(image_Y-starting_points(2)) + + area2filter = corrupted_image(x_index-choosing_distance(1):x_index+choosing_distance(2),... + y_index-choosing_distance(2):y_index+choosing_distance(2), :); + area2filter = im2double(area2filter).*255; + vectors_list = reshape(area2filter , [], 3)'; + + % Sorting Process + % In here, one array of vectors is created. First row will give + % us the distances calculated with VMF, second row will give us + % the angles calculated with BVDF. That's why there is "+2". + calculations = zeros(size(vectors_list, 1) + 3, size(vectors_list, 2)); + calculations(4:end, :) = vectors_list; + + for index = 1:size(vectors_list, 2) + for jndex = 1:size(vectors_list, 2) + + % For each pixel, we are choosing the window-size of + % pixels, and calculate the angles and distances from + % them. + + vectA = vectors_list(:, index); + vectB = vectors_list(:, jndex); + + if vectA == vectB + continue; + end + + % BVDF method for window-sized vectors. + calculations(3, index) = calculations(2, index) + ... + acosd(dot(vectA, vectB) / (norm(vectA) * norm(vectB))); + + % VMF method for window-sized vectors with Euclodien distances. + colorRed = (vectA(1) - vectB(1)).^(yValueVMF); + colorGreen = (vectA(2) - vectB(2)).^(yValueVMF); + colorBlue = (vectA(3) - vectB(3)).^(yValueVMF); + VMF_distance = (colorRed + colorGreen + colorBlue).^(1/yValueVMF); + calculations(2, index) = calculations(2, index) + VMF_distance; + + end + end + + % Combination of VMF and BVDF: Distance Directional Filter + calculations(1, :) = (calculations(3, :).^(BVDFratio)) .* (calculations(2, :).^(1-BVDFratio)); + + % Sorting the vectors inside the window, with the rules of BVDF + % and VMF. + [~, DDForder] = sort(calculations(1, :)); + DDFSortedVects = calculations(4:end, DDForder); + DDF_Vector = DDFSortedVects(:, 1); + + filtered_image(x_index, y_index, :) = DDF_Vector; + + end + end + + filtered_image = cast(filtered_image, 'uint8'); + + end + end + + methods (Access = private) + + function BVDFfilter(app) + app.FilteringStatusLamp.Color = app.LambColorWorking; + + app.FilteredImage = app.BasicVectorDirectionalFilter(app.NoisyImage, app.FilteringWindowSize); + + app.FilteredImageCanvas.ImageSource = app.FilteredImage; + app.FilteringStatusLamp.Color = app.LambColorFree; + end + + function VMFfilter(app) + app.FilteringStatusLamp.Color = app.LambColorWorking; + + app.FilteredImage = app.VectorMedianFilter(app.NoisyImage, app.FilteringWindowSize); + + app.FilteredImageCanvas.ImageSource = app.FilteredImage; + app.FilteringStatusLamp.Color = app.LambColorFree; + + end + + function DDFfilter(app) + app.FilteringStatusLamp.Color = app.LambColorWorking; + + app.FilteredImage = app.DistanceDirectionalFilter(... + app.NoisyImage, ... + app.FilteringWindowSize, ... + str2double(app.pValueTextBox.Value),... + str2double(app.yValueTextBox.Value)... + ); + + app.FilteredImageCanvas.ImageSource = app.FilteredImage; + app.FilteringStatusLamp.Color = app.LambColorFree; + end + end + + + % Callbacks that handle component events + methods (Access = private) + + % Code that executes after component creation + function startupFcn(app) + app.UIFigure.Name = 'Vectofil+'; + + app.ColorShowLamp.Color = app.NoiseColour./255; + app.RedSpinner.Value = app.NoiseColour(1); + app.GreenSpinner.Value = app.NoiseColour(2); + app.BlueSpinner.Value = app.NoiseColour(3); + app.NoiseText.Text = sprintf("%%%d", app.NoisePercentage); + end + + % Changes arrangement of the app based on UIFigure width + function updateAppLayout(app, event) + currentFigureWidth = app.UIFigure.Position(3); + if(currentFigureWidth <= app.onePanelWidth) + % Change to a 3x1 grid + app.GridLayout.RowHeight = {549, 549, 549}; + app.GridLayout.ColumnWidth = {'1x'}; + app.CenterPanel.Layout.Row = 1; + app.CenterPanel.Layout.Column = 1; + app.LeftPanel.Layout.Row = 2; + app.LeftPanel.Layout.Column = 1; + app.RightPanel.Layout.Row = 3; + app.RightPanel.Layout.Column = 1; + elseif (currentFigureWidth > app.onePanelWidth && currentFigureWidth <= app.twoPanelWidth) + % Change to a 2x2 grid + app.GridLayout.RowHeight = {549, 549}; + app.GridLayout.ColumnWidth = {'1x', '1x'}; + app.CenterPanel.Layout.Row = 1; + app.CenterPanel.Layout.Column = [1,2]; + app.LeftPanel.Layout.Row = 2; + app.LeftPanel.Layout.Column = 1; + app.RightPanel.Layout.Row = 2; + app.RightPanel.Layout.Column = 2; + else + % Change to a 1x3 grid + app.GridLayout.RowHeight = {'1x'}; + app.GridLayout.ColumnWidth = {335, '1x', 677}; + app.LeftPanel.Layout.Row = 1; + app.LeftPanel.Layout.Column = 1; + app.CenterPanel.Layout.Row = 1; + app.CenterPanel.Layout.Column = 2; + app.RightPanel.Layout.Row = 1; + app.RightPanel.Layout.Column = 3; + end + end + + % Button pushed function: InputImageBrowseButton + function InputImageBrowseButtonPushed(app, event) + % Get the location and image within a dialog window. + [in_img_name, in_img_location] = uigetfile({'*.png'; '*.jpg'; '*.jpeg';}); + app.ImageItself = imread(fullfile(in_img_location, in_img_name)); + + % Add the image to image canvas for user. + app.InputImageCanvas.ImageSource = app.ImageItself; + app.InputImageCanvas.Visible = 'on'; + app.InputImageCanvas.Enable = 'on'; + + % Show the radio button of noise. + app.NoiseWantSwitch.Visible = 'on'; + app.NoiseWantSwitch.Enable = 'on'; + + % Change the button name browse. + app.InputImageBrowseButton.Text = "Another!"; + + % Put the file location into the box of location. + app.ImageLocationTextBox.Value = fullfile(in_img_location, in_img_name); + + % Enable the selection of noise. + app.NoiseWantSwitch.Enable = 'on'; + + % Enable the filtering section. + app.WindowSizeKnob.Enable = 'on'; + app.PerformTheFilteringButton.Enable = 'on'; + app.FilteringStatusLamp.Enable = 'on'; + app.MethodSelectorKnob.Enable = 'on'; + app.SaveTheProcess.Enable = 'on'; + app.SaveTheResults.Enable = 'on'; + app.FilteringLabel.Enable = 'on'; + app.FilteringStatusLamp.Color = app.LambColorFree; + end + + % Value changed function: NoiseWantSwitch + function NoiseWantSwitchValueChanged(app, event) + value = app.NoiseWantSwitch.Value; + if (value == "Salt, pepper, noise!") + app.PercentageLabel.Enable = 'on'; + app.NoisePercentageSlider.Enable = 'on'; + + app.ColorShowLamp.Enable = 'on'; + app.ColourLabel.Enable = 'on'; + app.BlueLabel.Enable = 'on'; + app.BlueSpinner.Enable = 'on'; + app.RedLabel.Enable = 'on'; + app.RedSpinner.Enable = 'on'; + app.GreenLabel.Enable = 'on'; + app.GreenSpinner.Enable = 'on'; + + app.NoiseLabel.Enable = 'on'; + app.NoiseText.Enable = 'on'; + + app.PerformTheNoiseButton.Enable = 'on'; + else + app.PercentageLabel.Enable = 'off'; + app.NoisePercentageSlider.Enable = 'off'; + + app.ColorShowLamp.Enable = 'off'; + app.ColourLabel.Enable = 'off'; + app.BlueLabel.Enable = 'off'; + app.BlueSpinner.Enable = 'off'; + app.RedLabel.Enable = 'off'; + app.RedSpinner.Enable = 'off'; + app.GreenLabel.Enable = 'off'; + app.GreenSpinner.Enable = 'off'; + + app.NoiseLabel.Enable = 'off'; + app.NoiseText.Enable = 'off'; + + app.PerformTheNoiseButton.Enable = 'off'; + end + + end + + % Value changing function: RedSpinner + function RedSpinnerValueChanging(app, event) + changingValue = event.Value; + app.NoiseColour = [changingValue, app.NoiseColour(2), app.NoiseColour(3)]; + app.ColorShowLamp.Color = app.NoiseColour./255; + end + + % Value changing function: GreenSpinner + function GreenSpinnerValueChanging(app, event) + changingValue = event.Value; + app.NoiseColour = [app.NoiseColour(1), changingValue, app.NoiseColour(3)]; + app.ColorShowLamp.Color = app.NoiseColour./255; + end + + % Value changing function: BlueSpinner + function BlueSpinnerValueChanging(app, event) + changingValue = event.Value; + app.NoiseColour = [app.NoiseColour(1), app.NoiseColour(2), changingValue]; + app.ColorShowLamp.Color = app.NoiseColour./255; + end + + % Value changing function: NoisePercentageSlider + function NoisePercentageSliderValueChanging(app, event) + changingValue = event.Value; + app.NoisePercentage = changingValue; + app.NoiseText.Text = sprintf("%%%d", floor(app.NoisePercentage)); + end + + % Button pushed function: PerformTheNoiseButton + function PerformTheNoiseButtonPushed(app, event) + NoiseAddition(app); + app.NoisyImageCanvas.Visible = 'on'; + app.NoisyImageCanvas.Enable = 'on'; + app.WindowSizeKnob.Visible = 'on'; + app.WindowSizeKnob.Enable = 'on'; + app.FilteringStatusLamp.Enable = 'on'; + app.FilteringStatusLamp.Visible = 'on'; + end + + % Value changed function: WindowSizeKnob + function WindowSizeKnobValueChanged(app, event) + value = app.WindowSizeKnob.Value; + if (value == "Stop") + app.FilteringWindowSize = 3; + else + app.FilteringWindowSize = str2double(value); + end + end + + % Button pushed function: PerformTheFilteringButton + function PerformTheFilteringButtonPushed(app, event) + BVDFfilter(app); + app.FilteredImageCanvas.Enable = 'on'; + app.FilteredImageCanvas.Visible = 'on'; + app.SaveTheResults.Enable = 'on'; + app.SaveTheResults.Visible = 'on'; + app.SaveTheProcess.Enable = 'on'; + app.SaveTheProcess.Visible = 'on'; + end + + % Value changed function: MethodSelectorKnob + function MethodSelectorKnobValueChanged(app, event) + NewMethod = app.MethodSelectorKnob.Value; + if ~strcmpi(app.FilteringMethod, NewMethod) + app.FilteringMethod = NewMethod; + app.FilteredImage = zeros(size(app.ImageItself)); + app.FilteredImageCanvas.Visible = 'off'; + end + + if (app.FilteringMethod == "DDF") + app.yValueTextBox.Enable = 'on'; + app.yValueTextBox.Visible = 'on'; + app.yValueHelpText.Enable = 'on'; + app.yValueHelpText.Visible = 'on'; + app.yValueLabel.Enable = 'on'; + app.yValueLabel.Visible = 'on'; + + app.pValueSelector.Visible = 'on'; + app.pValueSelector.Enable = 'on'; + app.pValueLabel.Visible = 'on'; + app.pValueLabel.Enable = 'on'; + app.pValueText.Visible = 'on'; + app.pValueText.Enable = 'on'; + else + app.yValueTextBox.Enable = 'off'; + app.yValueTextBox.Visible = 'off'; + app.yValueHelpText.Enable = 'off'; + app.yValueHelpText.Visible = 'off'; + app.yValueLabel.Enable = 'off'; + app.yValueLabel.Visible = 'off'; + + app.pValueSelector.Visible = 'off'; + app.pValueSelector.Enable = 'off'; + app.pValueLabel.Visible = 'off'; + app.pValueLabel.Enable = 'off'; + app.pValueText.Visible = 'off'; + app.pValueText.Enable = 'off'; + end + end + + % Value changing function: pValueSelector + function pValueSelectorValueChanging(app, event) + changingValue = event.Value; + changingValue = changingValue/100; + app.DDFSettings(2) = changingValue; + app.pValueText.Text = sprintf("%%%d", floor(app.DDFSettings(2)*100)); + end + end + + % Component initialization + methods (Access = private) + + % Create UIFigure and components + function createComponents(app) + + % Create UIFigure and hide until all components are created + app.UIFigure = uifigure('Visible', 'off'); + app.UIFigure.AutoResizeChildren = 'off'; + app.UIFigure.Position = [100 100 1348 549]; + app.UIFigure.Name = 'MATLAB App'; + app.UIFigure.Resize = 'off'; + app.UIFigure.SizeChangedFcn = createCallbackFcn(app, @updateAppLayout, true); + + % Create GridLayout + app.GridLayout = uigridlayout(app.UIFigure); + app.GridLayout.ColumnWidth = {335, '1x', 677}; + app.GridLayout.RowHeight = {'1x'}; + app.GridLayout.ColumnSpacing = 0; + app.GridLayout.RowSpacing = 0; + app.GridLayout.Padding = [0 0 0 0]; + app.GridLayout.Scrollable = 'on'; + + % Create LeftPanel + app.LeftPanel = uipanel(app.GridLayout); + app.LeftPanel.Layout.Row = 1; + app.LeftPanel.Layout.Column = 1; + + % Create ImageLocationTextBox + app.ImageLocationTextBox = uieditfield(app.LeftPanel, 'text'); + app.ImageLocationTextBox.Placeholder = 'With some smile, please!'; + app.ImageLocationTextBox.Position = [21 371 192 22]; + + % Create InputImageBrowseButton + app.InputImageBrowseButton = uibutton(app.LeftPanel, 'push'); + app.InputImageBrowseButton.ButtonPushedFcn = createCallbackFcn(app, @InputImageBrowseButtonPushed, true); + app.InputImageBrowseButton.Position = [222 371 100 22]; + app.InputImageBrowseButton.Text = 'Browse'; + + % Create HellowelcometoLabel + app.HellowelcometoLabel = uilabel(app.LeftPanel); + app.HellowelcometoLabel.HorizontalAlignment = 'center'; + app.HellowelcometoLabel.FontSize = 25; + app.HellowelcometoLabel.FontWeight = 'bold'; + app.HellowelcometoLabel.Position = [25 492 226 31]; + app.HellowelcometoLabel.Text = 'Hello, welcome to '; + + % Create VectofilLabel + app.VectofilLabel = uilabel(app.LeftPanel); + app.VectofilLabel.HorizontalAlignment = 'center'; + app.VectofilLabel.FontSize = 35; + app.VectofilLabel.FontWeight = 'bold'; + app.VectofilLabel.Position = [25 450 150 43]; + app.VectofilLabel.Text = 'Vectofil+'; + + % Create PleasechooseanimagetoprocessLabel + app.PleasechooseanimagetoprocessLabel = uilabel(app.LeftPanel); + app.PleasechooseanimagetoprocessLabel.Position = [21 396 200 22]; + app.PleasechooseanimagetoprocessLabel.Text = 'Please choose an image to process.'; + + % Create MadeforComputerVisionandImageProcessingcourseinZUTLabel + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel = uilabel(app.LeftPanel); + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel.HorizontalAlignment = 'center'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel.FontSize = 10; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel.Position = [27 317 295 22]; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel.Text = {'Made for Computer Vision and Image Processing course in ZUT.'; 'License: GPL v2 (2021-2022 Fall)'}; + + % Create InputImageCanvas + app.InputImageCanvas = uiimage(app.LeftPanel); + app.InputImageCanvas.Enable = 'off'; + app.InputImageCanvas.Visible = 'off'; + app.InputImageCanvas.Position = [69 89 197 200]; + + % Create MadeforComputerVisionandImageProcessingcourseinZUTLabel_2 + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_2 = uilabel(app.LeftPanel); + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_2.HorizontalAlignment = 'center'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_2.FontSize = 10; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_2.FontWeight = 'bold'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_2.Position = [22 338 299 22]; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_2.Text = 'https://github.com/electricalgorithm/vectofil'; + + % Create MadeforComputerVisionandImageProcessingcourseinZUTLabel_3 + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_3 = uilabel(app.LeftPanel); + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_3.HorizontalAlignment = 'center'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_3.FontSize = 10; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_3.Position = [27 44 136 22]; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_3.Text = 'Twitter: @gkhnkcmrli'; + + % Create MadeforComputerVisionandImageProcessingcourseinZUTLabel_4 + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_4 = uilabel(app.LeftPanel); + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_4.HorizontalAlignment = 'center'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_4.FontSize = 10; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_4.Position = [183 44 138 22]; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_4.Text = 'LinkedIn: in/gokhankocmarli'; + + % Create MadeforComputerVisionandImageProcessingcourseinZUTLabel_5 + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_5 = uilabel(app.LeftPanel); + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_5.HorizontalAlignment = 'right'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_5.FontSize = 10; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_5.FontWeight = 'bold'; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_5.Position = [150 44 25 22]; + app.MadeforComputerVisionandImageProcessingcourseinZUTLabel_5.Text = '|'; + + % Create CenterPanel + app.CenterPanel = uipanel(app.GridLayout); + app.CenterPanel.Layout.Row = 1; + app.CenterPanel.Layout.Column = 2; + + % Create NoisePercentageSlider + app.NoisePercentageSlider = uislider(app.CenterPanel); + app.NoisePercentageSlider.ValueChangingFcn = createCallbackFcn(app, @NoisePercentageSliderValueChanging, true); + app.NoisePercentageSlider.Enable = 'off'; + app.NoisePercentageSlider.Position = [132 439 171 3]; + + % Create RedSpinner + app.RedSpinner = uispinner(app.CenterPanel); + app.RedSpinner.ValueChangingFcn = createCallbackFcn(app, @RedSpinnerValueChanging, true); + app.RedSpinner.Limits = [0 255]; + app.RedSpinner.RoundFractionalValues = 'on'; + app.RedSpinner.Enable = 'off'; + app.RedSpinner.Position = [123 359 64 22]; + + % Create GreenSpinner + app.GreenSpinner = uispinner(app.CenterPanel); + app.GreenSpinner.ValueChangingFcn = createCallbackFcn(app, @GreenSpinnerValueChanging, true); + app.GreenSpinner.Limits = [0 255]; + app.GreenSpinner.RoundFractionalValues = 'on'; + app.GreenSpinner.Enable = 'off'; + app.GreenSpinner.Position = [188 359 64 22]; + + % Create BlueSpinner + app.BlueSpinner = uispinner(app.CenterPanel); + app.BlueSpinner.ValueChangingFcn = createCallbackFcn(app, @BlueSpinnerValueChanging, true); + app.BlueSpinner.Limits = [0 255]; + app.BlueSpinner.RoundFractionalValues = 'on'; + app.BlueSpinner.Enable = 'off'; + app.BlueSpinner.Position = [253 359 64 22]; + + % Create ColourLabel + app.ColourLabel = uilabel(app.CenterPanel); + app.ColourLabel.WordWrap = 'on'; + app.ColourLabel.Enable = 'off'; + app.ColourLabel.Position = [27 359 93 22]; + app.ColourLabel.Text = 'Colour'; + + % Create RedLabel + app.RedLabel = uilabel(app.CenterPanel); + app.RedLabel.HorizontalAlignment = 'center'; + app.RedLabel.FontSize = 10; + app.RedLabel.Enable = 'off'; + app.RedLabel.Position = [125 338 62 22]; + app.RedLabel.Text = 'Red'; + + % Create GreenLabel + app.GreenLabel = uilabel(app.CenterPanel); + app.GreenLabel.HorizontalAlignment = 'center'; + app.GreenLabel.FontSize = 10; + app.GreenLabel.Enable = 'off'; + app.GreenLabel.Position = [187 338 62 22]; + app.GreenLabel.Text = 'Green'; + + % Create BlueLabel + app.BlueLabel = uilabel(app.CenterPanel); + app.BlueLabel.HorizontalAlignment = 'center'; + app.BlueLabel.FontSize = 10; + app.BlueLabel.Enable = 'off'; + app.BlueLabel.Position = [252 338 62 22]; + app.BlueLabel.Text = 'Blue'; + + % Create NoiseAdditionLabel + app.NoiseAdditionLabel = uilabel(app.CenterPanel); + app.NoiseAdditionLabel.HorizontalAlignment = 'center'; + app.NoiseAdditionLabel.FontSize = 25; + app.NoiseAdditionLabel.FontWeight = 'bold'; + app.NoiseAdditionLabel.Position = [29 44 175 31]; + app.NoiseAdditionLabel.Text = 'noise addition'; + + % Create UnderLineDesign + app.UnderLineDesign = uilabel(app.CenterPanel); + app.UnderLineDesign.HorizontalAlignment = 'center'; + app.UnderLineDesign.FontSize = 25; + app.UnderLineDesign.FontWeight = 'bold'; + app.UnderLineDesign.Position = [28 40 287 31]; + app.UnderLineDesign.Text = '____________________'; + + % Create NoiseWantSwitch + app.NoiseWantSwitch = uiswitch(app.CenterPanel, 'slider'); + app.NoiseWantSwitch.Items = {'No need for nosie.', 'Salt, pepper, noise!'}; + app.NoiseWantSwitch.ValueChangedFcn = createCallbackFcn(app, @NoiseWantSwitchValueChanged, true); + app.NoiseWantSwitch.Enable = 'off'; + app.NoiseWantSwitch.Position = [148 492 45 20]; + app.NoiseWantSwitch.Value = 'No need for nosie.'; + + % Create PercentageLabel + app.PercentageLabel = uilabel(app.CenterPanel); + app.PercentageLabel.WordWrap = 'on'; + app.PercentageLabel.Enable = 'off'; + app.PercentageLabel.Position = [27 429 93 22]; + app.PercentageLabel.Text = 'Percentage'; + + % Create NoisyImageCanvas + app.NoisyImageCanvas = uiimage(app.CenterPanel); + app.NoisyImageCanvas.Enable = 'off'; + app.NoisyImageCanvas.Visible = 'off'; + app.NoisyImageCanvas.Position = [56 90 226 201]; + + % Create PerformTheNoiseButton + app.PerformTheNoiseButton = uibutton(app.CenterPanel, 'push'); + app.PerformTheNoiseButton.ButtonPushedFcn = createCallbackFcn(app, @PerformTheNoiseButtonPushed, true); + app.PerformTheNoiseButton.Enable = 'off'; + app.PerformTheNoiseButton.Position = [123 304 188 22]; + app.PerformTheNoiseButton.Text = 'Perform the Noise'; + + % Create ColorShowLamp + app.ColorShowLamp = uilamp(app.CenterPanel); + app.ColorShowLamp.Enable = 'off'; + app.ColorShowLamp.Position = [101 360 20 20]; + app.ColorShowLamp.Color = [0 0 0]; + + % Create NoiseLabel + app.NoiseLabel = uilabel(app.CenterPanel); + app.NoiseLabel.FontWeight = 'bold'; + app.NoiseLabel.Enable = 'off'; + app.NoiseLabel.Position = [30 304 42 22]; + app.NoiseLabel.Text = 'Noise'; + + % Create NoiseText + app.NoiseText = uilabel(app.CenterPanel); + app.NoiseText.FontSize = 10; + app.NoiseText.Enable = 'off'; + app.NoiseText.Position = [72 304 49 22]; + app.NoiseText.Text = '%100'; + + % Create RightPanel + app.RightPanel = uipanel(app.GridLayout); + app.RightPanel.Layout.Row = 1; + app.RightPanel.Layout.Column = 3; + + % Create FilteringLabel + app.FilteringLabel = uilabel(app.RightPanel); + app.FilteringLabel.HorizontalAlignment = 'right'; + app.FilteringLabel.WordWrap = 'on'; + app.FilteringLabel.FontSize = 35; + app.FilteringLabel.FontWeight = 'bold'; + app.FilteringLabel.Position = [61 480 134 43]; + app.FilteringLabel.Text = 'filtering'; + + % Create WindowSizeKnob + app.WindowSizeKnob = uiknob(app.RightPanel, 'discrete'); + app.WindowSizeKnob.Items = {'3', '5', '7', '9'}; + app.WindowSizeKnob.ValueChangedFcn = createCallbackFcn(app, @WindowSizeKnobValueChanged, true); + app.WindowSizeKnob.Enable = 'off'; + app.WindowSizeKnob.Position = [69 380 64 64]; + app.WindowSizeKnob.Value = '3'; + + % Create FilteredImageCanvas + app.FilteredImageCanvas = uiimage(app.RightPanel); + app.FilteredImageCanvas.Enable = 'off'; + app.FilteredImageCanvas.Visible = 'off'; + app.FilteredImageCanvas.Position = [215 90 424 354]; + + % Create SaveTheResults + app.SaveTheResults = uibutton(app.RightPanel, 'push'); + app.SaveTheResults.Enable = 'off'; + app.SaveTheResults.Position = [355 44 108 22]; + app.SaveTheResults.Text = 'Save the Result'; + + % Create SaveTheProcess + app.SaveTheProcess = uibutton(app.RightPanel, 'push'); + app.SaveTheProcess.Enable = 'off'; + app.SaveTheProcess.Position = [470 44 124 22]; + app.SaveTheProcess.Text = 'Save The Process'; + + % Create PerformTheFilteringButton + app.PerformTheFilteringButton = uibutton(app.RightPanel, 'push'); + app.PerformTheFilteringButton.ButtonPushedFcn = createCallbackFcn(app, @PerformTheFilteringButtonPushed, true); + app.PerformTheFilteringButton.Enable = 'off'; + app.PerformTheFilteringButton.Position = [23 44 313 22]; + app.PerformTheFilteringButton.Text = 'Perform the Filtering'; + + % Create WindowSizeLabel + app.WindowSizeLabel = uilabel(app.RightPanel); + app.WindowSizeLabel.HorizontalAlignment = 'center'; + app.WindowSizeLabel.FontWeight = 'bold'; + app.WindowSizeLabel.Enable = 'off'; + app.WindowSizeLabel.Position = [61 347 79 22]; + app.WindowSizeLabel.Text = 'Window Size'; + + % Create MethodSelectorKnob + app.MethodSelectorKnob = uiknob(app.RightPanel, 'discrete'); + app.MethodSelectorKnob.Items = {'VMF', 'BVDF', 'DDF'}; + app.MethodSelectorKnob.ValueChangedFcn = createCallbackFcn(app, @MethodSelectorKnobValueChanged, true); + app.MethodSelectorKnob.Enable = 'off'; + app.MethodSelectorKnob.Position = [69 247 64 64]; + app.MethodSelectorKnob.Value = 'VMF'; + + % Create FilteringStatusLamp + app.FilteringStatusLamp = uilamp(app.RightPanel); + app.FilteringStatusLamp.Enable = 'off'; + app.FilteringStatusLamp.Position = [27 485 27 27]; + app.FilteringStatusLamp.Color = [1 0 0]; + + % Create MethodLabel + app.MethodLabel = uilabel(app.RightPanel); + app.MethodLabel.HorizontalAlignment = 'center'; + app.MethodLabel.FontWeight = 'bold'; + app.MethodLabel.Enable = 'off'; + app.MethodLabel.Position = [77 214 48 22]; + app.MethodLabel.Text = 'Method'; + + % Create yValueHelpText + app.yValueHelpText = uilabel(app.RightPanel); + app.yValueHelpText.HorizontalAlignment = 'right'; + app.yValueHelpText.WordWrap = 'on'; + app.yValueHelpText.FontSize = 10; + app.yValueHelpText.Visible = 'off'; + app.yValueHelpText.Position = [27 157 177 22]; + app.yValueHelpText.Text = {'2 for Eucledean, 1 for Manhatten'; ''}; + + % Create yValueTextBox + app.yValueTextBox = uieditfield(app.RightPanel, 'numeric'); + app.yValueTextBox.Limits = [1 999]; + app.yValueTextBox.ValueDisplayFormat = '%.2f'; + app.yValueTextBox.Visible = 'off'; + app.yValueTextBox.Position = [156 178 48 22]; + app.yValueTextBox.Value = 2; + + % Create pValueLabel + app.pValueLabel = uilabel(app.RightPanel); + app.pValueLabel.Enable = 'off'; + app.pValueLabel.Visible = 'off'; + app.pValueLabel.Position = [23 124 116 22]; + app.pValueLabel.Text = 'Percentage of BVDF'; + + % Create pValueSelector + app.pValueSelector = uislider(app.RightPanel); + app.pValueSelector.ValueChangingFcn = createCallbackFcn(app, @pValueSelectorValueChanging, true); + app.pValueSelector.Enable = 'off'; + app.pValueSelector.Visible = 'off'; + app.pValueSelector.Position = [25 114 173 3]; + + % Create pValueText + app.pValueText = uilabel(app.RightPanel); + app.pValueText.FontWeight = 'bold'; + app.pValueText.Enable = 'off'; + app.pValueText.Visible = 'off'; + app.pValueText.Position = [160 124 49 22]; + app.pValueText.Text = '%0'; + + % Create yValueLabel + app.yValueLabel = uilabel(app.RightPanel); + app.yValueLabel.Enable = 'off'; + app.yValueLabel.Visible = 'off'; + app.yValueLabel.Position = [23 178 87 22]; + app.yValueLabel.Text = 'y Value of VMF'; + + % Show the figure after all components are created + app.UIFigure.Visible = 'on'; + end + end + + % App creation and deletion + methods (Access = public) + + % Construct app + function app = vectofil_plus + + % Create UIFigure and components + createComponents(app) + + % Register the app with App Designer + registerApp(app, app.UIFigure) + + % Execute the startup function + runStartupFcn(app, @startupFcn) + + if nargout == 0 + clear app + end + end + + % Code that executes before app deletion + function delete(app) + + % Delete UIFigure when app is deleted + delete(app.UIFigure) + end + end +end \ No newline at end of file

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