color_enhance_python.zip

import os, sys import cv2, time import numpy as np # 色彩增强 def color_enhance(image): # 转换颜色空间到CMY image_BGR = image.copy() image_CMY = 255 - image_BGR # 找CMY空间中最小值 image_min = image_CMY[:,:,0].copy() image_min[image_CMY[:,:,0]>image_CMY[:,:,1]] = image_CMY[:,:,1][image_CMY[:,:,0]>image_CMY[:,:,1]] image_min[image_min>image_CMY[:,:,2]] = image_CMY[:,:,2][image_min>image_CMY[:,:,2]] # 减去最小值 image_CMY[:,:,0] = image_CMY[:,:,0] - image_min image_CMY[:,:,1] = image_CMY[:,:,1] - image_min image_CMY[:,:,2] = image_CMY[:,:,2] - image_min # 转换得到的CMY图像到HSV空间 image_HSV = cv2.cvtColor(image_CMY, cv2.COLOR_BGR2HSV) # 找V信道极大极小值，极大值可调整最终色彩鲜艳程度 max_v = np.max(image_HSV[:,:,2]) / 255.0 min_v = np.min(image_HSV[:,:,2]) / 255.0 # 重新量化V值 image_HSV[:,:,2] = ((image_HSV[:,:,2]/255.0 - min_v) / (max_v - min_v)) * 255.0 image_HSV[:,:,2][image_HSV[:,:,2] > 255] = 255 image_HSV[:,:,2][image_HSV[:,:,2] < 0] = 0 # HSV->BGR，注意此时result_image值范围为0-255，超过值会自动减-255 result_image = cv2.cvtColor(image_HSV, cv2.COLOR_HSV2BGR) result_image = result_image / 255 result_image[:,:,0] = result_image[:,:,0] + image_min / 255 result_image[:,:,1] = result_image[:,:,1] + image_min / 255 result_image[:,:,2] = result_image[:,:,2] + image_min / 255 result_image[result_image <= 1] = 1 - result_image[result_image <= 1] result_image[result_image > 1] = 0.0 result_image = (result_image*255).astype(np.uint8) return result_image if __name__ == '__main__': image = cv2.imread('test_img.jpg') color_image = color_enhance(image) cv2.imshow('result', color_image) cv2.waitKey(0)