15图像的灰度线性变换

#https://blog.csdn.net/Eastmount/article/details/88858696

一.图像灰度线性变换原理

也就是线性变换

img = cv2.imread('C:/Users/31035/Desktop/yifei/01.jpg')
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#直接广播做加法，虽然简单，不过不好调节。
img = img + 80#图片花了
#显示图像
cv2.imshow("img", img)
#等待显示
cv2.waitKey(0)
cv2.destroyAllWindows()

二.图像灰度上移变换

img = cv2.imread('C:/Users/31035/Desktop/yifei/01.jpg')
#图像灰度转换
grayImage = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

#获取图像高度和宽度
height = grayImage.shape[0]
width = grayImage.shape[1]

#创建一幅图像
result = np.zeros((height, width), np.uint8)

#图像灰度上移变换 DB=DA+50
for i in range(height):
    for j in range(width):
        
        if (int(grayImage[i,j]+80) > 255):
            gray = 255
        else:
            gray = int(grayImage[i,j]+80)
            
        result[i,j] = np.uint8(gray)

#显示图像
cv2.imshow("Gray Image", grayImage)
cv2.imshow("Result", result)

#等待显示
cv2.waitKey(0)
cv2.destroyAllWindows()

三.图像对比度增强变换

替换一段代码

if (int(grayImage[i,j]*1.5) > 255):
            gray = 255
        else:
            gray = int(grayImage[i,j]*1.5)
            
        result[i,j] = np.uint8(gray)

四.图像对比度减弱变换

乘以小于1的系数即可

五.图像灰度反色变换

#图像灰度反色变换 DB=255-DA
for i in range(height):
    for j in range(width):
        gray = 255 - grayImage[i,j]
        result[i,j] = np.uint8(gray)