contrast enhacement implementation

Author: bryanidem

ImageProcessingScripts/Contrast Enhancement/README.md

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+# Contrast enhancement image
+
+Using the histogram equalization, we can enhance the contrast in low contrast images. This algorithm uses the cummulative distribution function to map the intensities of a low distribuited histogram into a one more spreaded. Have a look to this [explanation](https://en.wikipedia.org/wiki/Histogram_equalization)
+
+![output example](example.png)
+
+## Requirements
+
+This program only uses the libraries
+
+- Numpy
+- Matplotlib
+
+## Running the code
+
+inside of the `Contrast enhancement` folder run:
+
+> `python3 contrast_enhancement.py`

ImageProcessingScripts/Contrast Enhancement/contrast_enhancement.py

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+import numpy as np
+import matplotlib.pyplot as plt
+
+def rgb2gray(rgb_img):
+    "convert an RGB image into single channel grayscale image"
+    r, g, b = rgb_img[:, :, 0], rgb_img[:, :, 1], rgb_img[:, :, 2]
+    gray = 0.2989 * r + 0.5870 * g + 0.1140 * b
+    return gray
+
+
+def histogram_equalization(img):
+    """mapping of a low contrast histogram into one with high contrast
+     using the cummulative distribution function(cdf)"""
+    img = rgb2gray(img).astype('int')
+    #transform the image into 1D for better performance
+    img_1D = img.ravel()
+    hist, _ = np.histogram(img_1D, 256, density=True)
+    bins = np.array(range(256))
+    histNorm = hist/hist.size
+    cdf = (histNorm.cumsum()*255**2).astype('int')
+    output = np.zeros(img.size)
+    #mapping of each pixel into better contrast hist
+    for i in range(img.size):
+        output[i] = cdf[img_1D[i]]
+    output = np.reshape(output, img.shape)
+    return output
+
+def show_images(img, output):
+    """compare the input and output images"""
+    plt.figure()
+    plt.subplot(121), plt.imshow(img, cmap='gray'), plt.title('original image'), plt.axis('off')
+    plt.subplot(122), plt.imshow(output, cmap='gray'), plt.title('contrast enhancement img'), plt.axis('off')
+    plt.show()
+
+if __name__ == '__main__':
+    img = plt.imread('images/lumbar_spine.jpg')
+    output = histogram_equalization(img)
+    show_images(img, output)

ImageProcessingScripts/Contrast Enhancement/example.png

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+numpy
+matplotlib