Image Processing & Computer Vision Projects

NOTE: Click on the images to view them full-size.

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1_Contrast Adjustment link

Histogram_Equalization

• Implementation of the Histogram Equalization algorithm, applied only to the pixels inside the circle in the image.

Contrast_Stretching

• Implementation of the Contrast Stretching algorithm applied to the image.

Compare

• Comparison of Histogram Equalization and Contrast Stretching algorithms.

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2_Image Filtering (Denoising, Sharpening, Deblurring) link

Notch

• Implementation of the Notch Filter algorithm applied to the image.

Wiener

• In this algorithm, we applied the Wiener Filter to each of the RGB bands separately and, finally, merged the filtered bands to obtain the final image.

Highboost

• In this algorithm, we applied the High Boost to each of the RGB bands separately and, finally, merged the filtered bands to obtain the final image.

Unsharp

• In this algorithm, we applied the Unsharp Masking to each of the RGB bands separately and, finally, merged the filtered bands to obtain the final image.

Median

• Implementation of the Median algorithm applied to the image.

Adaptive_Median

• Implementation of the Adaptive Median algorithm applied to the image.

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3_Content-Based Image Retrieval (CBIR) System link

RGB_CBIR

• Content-based image retrieval system by using RGB color histogram.

HSV_CBIR

• Content-based image retrieval system by using HSV color histogram.

RGB_CBIR_Half

• Content-based image retrieval system by using RGB color histogram on half of the image.

HSV_CBIR_Half

• Content-based image retrieval system by using HSV color histogram on half of the image.

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4_Image Pyramids & Blending link

Hybrid_Fourier

• Creating the Hybrid Image using the Fast Fourier Transform (FFT).

Hybrid_Pyramid

• Creating the Hybrid Image using the Laplacian Pyramids.

Blend_Pyramid

• Creating the Blended Image using the Laplacian Pyramids.

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5_Scale-Invariant Feature Transform (SIFT) Algorithm link

SIFT_v1

• This algorithm selects an image, applies changes (rotation, resizing) to it, and then extracts and displays the SIFT features of both images.

SIFT_v2

• This algorithm selects an image, applies changes (rotation, resizing) to it, and then displays the corresponding SIFT features of both images.

CBIR_SIFT_trainHist & CBIR_SIFT_main

• Improves Content-Based Image Retrieval (CBIR) using Scale-Invariant Feature Transform (SIFT). This involves CBIR using a 3D histogram (left images) and rectified ranking using SIFT (right images).

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6_Gradient Domain Fusion (Poisson Blending, Mixed Gradient) link

Gradient_Blend

• Implementation of the Poisson Blending and Mixed Gradient algorithms.

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7_Camera Calibration with OpenCV link

Camera_Calibration

• Implements the Camera Calibration method with OpenCV.
  • This program has two modes:
    1. Images are captured directly from the camera, and camera distortion is removed in real-time. This mode includes two stages: Train (extracting camera parameters) and Test (simultaneously displaying the original and corrected images).
    2. Images are selected from an image folder, and the corrected image is displayed and saved in the output folder.

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