OpenCV-Python 彩色图像均衡化与规定化（OpenCV-Python-Toturial-中文版.pdf）

OpenCV-Python 彩色图像均衡化与规定化（OpenCV-Python-Toturial-中文版.pdf）

彩色图像均衡化

在HSI空间对亮度分量进行均衡化

def method_one(): img = cv2.imread('../assets/Fig6.png') his = cv2.cvtColor(img, cv2.COLOR_RGB2HLS) cv2.imshow('img', img) his_i = his[:, :, 1] equal_i = cv2.equalizeHist(hsl_i) his[:, :, 1] = equal_i dst = cv2.cvtColor(his, cv2.COLOR_HLS2BGR) cv2.imshow('dst', dst) cv2.waitKey(0) cv2.destroyAllWindows()

对彩色图像的R，G，B三通道进行均衡化

def method_two(): img = cv2.imread('../assets/Fig6.png') (b, g, r) = cv2.split(img) equal_b = cv2.equalizeHist(b) equal_g = cv2.equalizeHist(g) equal_r = cv2.equalizeHist(r) dst = cv2.merge((equal_b, equal_g, equal_r)) cv2.imshow('img', img) cv2.imshow('dst', dst) cv2.waitKey(0) cv2.destroyAllWindows()

对彩色图像进行规定话

现在有两幅图，FigA 和 FigB，现在要对FigA进行规定化，使FigA 图像的直方图规范化最接近FigB的情况。

def method_three(): img = cv2.imread('../assets/Fig6A.jpg') dst = cv2.imread('../assets/Fig6B.jpg') def_img = cv2.imread('../assets/Fig6A.jpg') color = ('b', 'g', 'r') for i, col in enumerate(color): hist1, bins = np.histogram(img[:, :, i].ravel(), 256, [0, 256]) hist2, bins = np.histogram(dst[:, :, i].ravel(), 256, [0, 256]) # 获得累计直方图 cdf1 = hist1.cumsum() cdf2 = hist2.cumsum() # 归一化处理 cdf1_hist = hist1.cumsum() / cdf1.max() cdf2_hist = hist2.cumsum() / cdf2.max() # diff_cdf 里是每2个灰度值比率间的差值 diff_cdf = [0]*256 for j in range(256): for k in range(256): diff_cdf[j][k] = abs(cdf1_hist[j] - cdf2_hist[k]) # FigA 中的灰度级与目标灰度级的对应表 lut = np.zeros(256, dtype=np.int) for j in range(256): squ_min = diff_cdf[j][0] index = 0 for k in range(256): if squ_min > diff_cdf[j][k]: squ_min = diff_cdf[j][k] index = k lut[j] = ([j, index]) h = int(img.shape[0]) w = int(dst.shape[1]) # 对原图像进行灰度值的映射 for j in range(h): for k in range(w): def_img[j, k, i] = lut[img[j, k, i]][1] cv2.namedWindow('Fig6A', 0) cv2.resizeWindow('Fig6A', 400, 520) cv2.namedWindow('Fig6B', 0) cv2.resizeWindow('Fig6B', 400, 520) cv2.namedWindow('def', 0) cv2.resizeWindow('def', 400, 520) cv2.imshow('Fig6A', img) cv2.imshow('Fig6B', dst) cv2.imshow('def', def_img) cv2.waitKey(0) cv2.destroyAllWindows()

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