python numpy opencv调整图片亮度对比度饱和度

（想要完整代码直接划到最后）

原理比较简单，本质上是对图像各个通道的每个像素点做线性变换，对超出范围[0,255]的做截断处理，所以使用numpy处理比较方便

安装依赖库

pip install numpy
pip install opencv-python

亮度变换

# 修改图像的亮度，brightness取值0～2 <1表示变暗 >1表示变亮
def change_brightness(img, brightness):
    [averB, averG, averR] = np.array(cv2.mean(img))[:-1] / 3
    k = np.ones((img.shape))
    k[:, :, 0] *= averB
    k[:, :, 1] *= averG
    k[:, :, 2] *= averR
    img = img + (brightness - 1) * k
    img[img > 255] = 255
    img[img < 0] = 0
    return img.astype(np.uint8)

一下函数为了方便展示调用，可自行选择使用

def cvshow(name, img):
    cv2.namedWindow(name, cv2.WINDOW_NORMAL)
    cv2.resizeWindow(name,1280,720)
    cv2.imshow(name, img)
    cv2.waitKey(0)
    cv2.destroyWindow(name)

对"sc/1.jpg"应用亮度变换

    img = cv2.imread("sc/1.jpg")
    img = change_brightness(img,2)
    cv2.imwrite("sc/2.jpg",img)
    cvshow("change_brightness",img)

应用前

应用后

效果还是比较明显的

对比度变换

# 修改图像的对比度,coefficent>0, <1降低对比度,>1提升对比度 建议0-2
def change_contrast(img, coefficent):
    imggray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    m = cv2.mean(img)[0]
    graynew = m + coefficent * (imggray - m)
    img1 = np.zeros(img.shape, np.float32)
    k = np.divide(graynew, imggray, out=np.zeros_like(graynew), where=imggray != 0)
    img1[:, :, 0] = img[:, :, 0] * k
    img1[:, :, 1] = img[:, :, 1] * k
    img1[:, :, 2] = img[:, :, 2] * k
    img1[img1 > 255] = 255
    img1[img1 < 0] = 0
    return img1.astype(np.uint8)

对路径"sc/1.jpg"下图片应用对比度变换实例：

    img = cv2.imread("sc/1.jpg")
    img = change_contrast(img,2)
    cv2.imwrite("sc/2.jpg",img)
    cvshow("change_brightness",img)

应用前

应用后

综合调整(完整代码)

为了方便使用，我们创建两个滑块对竖直进行控制，而后按s键进行保存

import cv2
import numpy as np

# 修改图像的对比度,coefficent>0, <1降低对比度,>1提升对比度 建议0-2
def change_contrast(img, coefficent):
    imggray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    m = cv2.mean(img)[0]
    graynew = m + coefficent * (imggray - m)
    img1 = np.zeros(img.shape, np.float32)
    k = np.divide(graynew, imggray, out=np.zeros_like(graynew), where=imggray != 0)
    img1[:, :, 0] = img[:, :, 0] * k
    img1[:, :, 1] = img[:, :, 1] * k
    img1[:, :, 2] = img[:, :, 2] * k
    img1[img1 > 255] = 255
    img1[img1 < 0] = 0
    return img1.astype(np.uint8)

# 修改图像的亮度，brightness取值0～2 <1表示变暗 >1表示变亮
def change_brightness(img, brightness):
    [averB, averG, averR] = np.array(cv2.mean(img))[:-1] / 3
    k = np.ones((img.shape))
    k[:, :, 0] *= averB
    k[:, :, 1] *= averG
    k[:, :, 2] *= averR
    img = img + (brightness - 1) * k
    img[img > 255] = 255
    img[img < 0] = 0
    return img.astype(np.uint8)

def cvshow(name, img):
    cv2.namedWindow(name, cv2.WINDOW_NORMAL)
    cv2.resizeWindow(name,1280,720)
    cv2.imshow(name, img)
    cv2.waitKey(0)
    cv2.destroyWindow(name)

def demo():
    # 加载图片 读取彩色图像
    image = cv2.imread('sc/1.jpg',cv2.IMREAD_COLOR)
    l = 50
    c = 50
    MAX_VALUE = 100
    # 调节饱和度和亮度的窗口
    cv2.namedWindow("changImage", cv2.WINDOW_AUTOSIZE)

    def nothing(*arg):
        pass

    # 滑动块
    cv2.createTrackbar("l", "changImage", l, MAX_VALUE, nothing)
    cv2.createTrackbar("c", "changImage", c, MAX_VALUE, nothing)
    while True:
        # 得到 l、 s 、c的值
        l = cv2.getTrackbarPos('l', "changImage")
        c = cv2.getTrackbarPos('c', "changImage")
        img = np.copy(image.astype(np.float32))
        # 亮度 -1~1
        img = change_brightness(img, float(l - 50) / float(50))
        # 对比度 0~2
        img = change_contrast(img, c / 50)

        # 显示调整后的效果
        img = cv2.resize(img, (1280, 720))
        cv2.imshow("changImage", img)
        ch = cv2.waitKey(5)
        # 按 ESC 键退出
        if ch == 27:
            break
        elif ch == ord('s'):
            # 按 s 键保存并退出
            # 保存结果
            cv2.imwrite("result.jpg", img)
            break

    # 关闭所有的窗口
    cv2.destroyAllWindows()


if __name__ == "__main__":
    demo()

效果