zinating
diff --git a/‎digital_image_processing/histogram_equalization/histogram_stretch.py‎
Lines changed: 65 additions & 0 deletions b/‎digital_image_processing/histogram_equalization/histogram_stretch.py‎
Lines changed: 65 additions & 0 deletions
diff --git a/‎digital_image_processing/histogram_equalization/image_data/input.jpg‎
58.7 KB b/‎digital_image_processing/histogram_equalization/image_data/input.jpg‎
58.7 KB
diff --git a/‎digital_image_processing/histogram_equalization/output_data/output.jpg‎
116 KB b/‎digital_image_processing/histogram_equalization/output_data/output.jpg‎
116 KB
@@ -0,0 +1,65 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Sep 28 15:22:29 2018
+
+@author: Binish125
+"""
+import copy
+import os
+
+import numpy as np
+
+import cv2
+import matplotlib.pyplot as plt
+
+
+class contrastStretch:
+    def __init__(self):
+        self.img = ""
+        self.original_image = ""
+        self.last_list = []
+        self.rem = 0
+        self.L = 256
+        self.sk = 0
+        self.k = 0
+        self.number_of_rows = 0
+        self.number_of_cols = 0
+
+    def stretch(self, input_image):
+        self.img = cv2.imread(input_image, 0)
+        self.original_image = copy.deepcopy(self.img)
+        x, _, _ = plt.hist(self.img.ravel(), 256, [0, 256], label="x")
+        self.k = np.sum(x)
+        for i in range(len(x)):
+            prk = x[i] / self.k
+            self.sk += prk
+            last = (self.L - 1) * self.sk
+            if self.rem != 0:
+                self.rem = int(last % last)
+            last = int(last + 1 if self.rem >= 0.5 else last)
+            self.last_list.append(last)
+            self.number_of_rows = int(np.ma.count(self.img) / self.img[1].size)
+            self.number_of_cols = self.img[1].size
+        for i in range(self.number_of_cols):
+            for j in range(self.number_of_rows):
+                num = self.img[j][i]
+                if num != self.last_list[num]:
+                    self.img[j][i] = self.last_list[num]
+        cv2.imwrite("output_data/output.jpg", self.img)
+
+    def plotHistogram(self):
+        plt.hist(self.img.ravel(), 256, [0, 256])
+
+    def showImage(self):
+        cv2.imshow("Output-Image", self.img)
+        cv2.imshow("Input-Image", self.original_image)
+        cv2.waitKey(5000)
+        cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    file_path = os.path.join(os.path.basename(__file__), "image_data/input.jpg")
+    stretcher = contrastStretch()
+    stretcher.stretch(file_path)
+    stretcher.plotHistogram()
+    stretcher.showImage()