线性灯光混合python_Python_Opencv_Image Processing

线性灯光混合python

python opencv image-processing

线性灯光混合python,python,opencv,image-processing,Python,Opencv,Image Processing,我用openCV Python创建了一个高通滤波器，现在我想把它和线性光模式混合在一起像photoshop混合这里有两种方法可以使用Python/OpenCV从高通过滤图像中进行线性灯光混合。第一种方法应用创建过滤器并将其应用于颜色输入图像。第二种方法与之相同，但使用HSV的V通道。然后将其转换回BGR 输入：方法1：应用于BGR图像 import cv2 import numpy as np # read image and convert to float in range 0 t

我用openCV Python创建了一个高通滤波器，现在我想把它和线性光模式混合在一起

像photoshop混合

这里有两种方法可以使用Python/OpenCV从高通过滤图像中进行线性灯光混合。第一种方法应用创建过滤器并将其应用于颜色输入图像。第二种方法与之相同，但使用HSV的V通道。然后将其转换回BGR

输入：

方法1：应用于BGR图像

import cv2 import numpy as np # read image and convert to float in range 0 to 1 img = cv2.imread('man_red_shirt.jpg').astype("float32") / 255.0 # create high pass filter # blur image then subtract from img blur = cv2.GaussianBlur(img, (3,3), 0) hipass = img - blur + 0.5 # apply linear light blending #http://www.simplefilter.de/en/basics/mixmods.html linear_light = (2 * img + hipass - 1) result = (255 * linear_light).clip(0, 255).astype(np.uint8) # save results cv2.imwrite('man_red_shirt_linear_light.jpg', result) # show results cv2.imshow('hipass', hipass) cv2.imshow('result', result) cv2.waitKey(0) cv2.destroyAllWindows()

import cv2 import numpy as np # read image and convert to float in range 0 to 1 img = cv2.imread('man_red_shirt.jpg').astype("float32") / 255.0 # convert to hsv hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) # separate channels h,s,v = cv2.split(hsv) # create high pass filter from the v channel # blur v channel then subtract from v blur = cv2.GaussianBlur(v, (3,3), 0) hipass = v - blur + 0.5 # apply linear light blending to v channel #http://www.simplefilter.de/en/basics/mixmods.html v_linear_light = (2 * v + hipass - 1) # recombine hsv2 = cv2.merge([h,s,v_linear_light]) # convert back to bgr bgr = cv2.cvtColor(hsv2, cv2.COLOR_HSV2BGR) # result = (255 * bgr).clip(0, 255).astype(np.uint8) # save results cv2.imwrite('man_red_shirt_linear_light2.jpg', result) # show results cv2.imshow('hipass', hipass) cv2.imshow('result', result) cv2.waitKey(0) cv2.destroyAllWindows()

方法2：适用于HSV图像的V通道

import cv2 import numpy as np # read image and convert to float in range 0 to 1 img = cv2.imread('man_red_shirt.jpg').astype("float32") / 255.0 # create high pass filter # blur image then subtract from img blur = cv2.GaussianBlur(img, (3,3), 0) hipass = img - blur + 0.5 # apply linear light blending #http://www.simplefilter.de/en/basics/mixmods.html linear_light = (2 * img + hipass - 1) result = (255 * linear_light).clip(0, 255).astype(np.uint8) # save results cv2.imwrite('man_red_shirt_linear_light.jpg', result) # show results cv2.imshow('hipass', hipass) cv2.imshow('result', result) cv2.waitKey(0) cv2.destroyAllWindows()

import cv2 import numpy as np # read image and convert to float in range 0 to 1 img = cv2.imread('man_red_shirt.jpg').astype("float32") / 255.0 # convert to hsv hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) # separate channels h,s,v = cv2.split(hsv) # create high pass filter from the v channel # blur v channel then subtract from v blur = cv2.GaussianBlur(v, (3,3), 0) hipass = v - blur + 0.5 # apply linear light blending to v channel #http://www.simplefilter.de/en/basics/mixmods.html v_linear_light = (2 * v + hipass - 1) # recombine hsv2 = cv2.merge([h,s,v_linear_light]) # convert back to bgr bgr = cv2.cvtColor(hsv2, cv2.COLOR_HSV2BGR) # result = (255 * bgr).clip(0, 255).astype(np.uint8) # save results cv2.imwrite('man_red_shirt_linear_light2.jpg', result) # show results cv2.imshow('hipass', hipass) cv2.imshow('result', result) cv2.waitKey(0) cv2.destroyAllWindows()

请以相同分辨率分别发布原始输入图像和高通图像（而不是屏幕快照）