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介绍

YUV：Y分量确定颜色的亮度（称为亮度或亮度），而U和V分量确定颜色本身（色度）

import cv2 as cvimport matplotlib.pyplot as pltimg = cv.imread('../images/scene_001.jpg')yuv = cv.cvtColor(img, cv.COLOR_BGR2YUV)y_img = yuv.copy()y_const = 255y_img[:, :, 1] = y_consty_img[:, :, 2] = y_constu_img = yuv.copy()u_img[:, :, 0] = y_constu_img[:, :, 2] = y_constv_img = yuv.copy()v_img[:, :, 0] = y_constv_img[:, :, 1] = y_constfig, ax = plt.subplots(2, 2, figsize=(8, 8))ax[0][0].set_title('origin')ax[0][0].imshow(cv.cvtColor(yuv, cv.COLOR_YUV2RGB))ax[0][1].set_title('y channel')ax[0][1].imshow(y_img[:, :, 0], cmap='gray')ax[1][0].set_title('u channel(y=' + str(y_const) + ')')ax[1][0].imshow(cv.cvtColor(u_img, cv.COLOR_YUV2RGB))ax[1][1].set_title('v channel(y=' + str(y_const) + ')')ax[1][1].imshow(cv.cvtColor(v_img, cv.COLOR_YUV2RGB))[axi.axis('off') for axi in ax.ravel()]plt.show()

代码实现（Python）

import cv2 as cvimport numpy as npimport matplotlib.pyplot as pltimg = cv.imread('../images/scene_001.jpg')yuv = cv.cvtColor(img, cv.COLOR_BGR2YUV)hist_size = 256"""calcHist(images, channels, mask, histSize, ranges[, hist[, accumulate]]) -> hist"""y_hist = np.array(cv.calcHist(img, [0], None, [hist_size], [0, hist_size - 1])).reshape(hist_size)fig, ax = plt.subplots(5, 2, figsize=(8, 8))ax[0][0].set_title('origin')ax[0][0].imshow(cv.cvtColor(img, cv.COLOR_BGR2RGB))ax[0][0].axis('off')ax[0][1].set_title('y hist')ax[0][1].hist(y_hist, 50)# Equalize histdef equalize(adjust_ratio, ii):    rows, cols, _ = img.shape    y_hist_equal = y_hist    total = 0    for i in range(len(y_hist)):        total += y_hist[i]        tmp = total * 255 / rows / cols        y_hist_equal[i] = int(min(max((tmp - i) * adjust_ratio + i, 0), 255))    yuv_equal = yuv.copy()    for row in yuv_equal:        for col in row:            col[0] = y_hist_equal[int(col[0])]    y_hist_equal = np.array(cv.calcHist(yuv_equal, [0], None, [hist_size], [0, hist_size - 1])).reshape(hist_size)    ax[ii][0].set_title('Equalize(ratio=' + str(adjust_ratio) + ')')    ax[ii][0].imshow(cv.cvtColor(yuv_equal, cv.COLOR_YUV2RGB))    ax[ii][0].axis('off')    ax[ii][1].set_title('Equalized y hist')    ax[ii][1].hist(y_hist_equal, 50)equalize(0, 1)equalize(0.33, 2)equalize(0.66, 3)equalize(1, 4)plt.show()

所谓的直方图均衡化，其实就是让y值多的点越来越多，y值少的点越来越少，穷者越穷，富者越富，对比度就会越来越大，区别就越大

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