问题

如何调整彩色图像的饱和度和亮度

解决思路

详细步骤：

1. 将RGB图像值归一化到[0, 1]
2. 然后使用函数cvtColor进行色彩空间的转换
3. 接下来可以根据处理灰度图像对比度增强伽马变换或者线性变换调整饱和度和亮度分量
4. 最后转换到RGB色彩空间

代码

# !/usr/bin/env python
# -*-encoding: utf-8-*-
# author:LiYanwei
# version:0.1


import numpy as np
import cv2


def main():
    # 加载图片 读取彩色图像
    image = cv2.imread('./Files_image/img1.jpg', cv2.IMREAD_COLOR)
    # print(image)
    # cv2.imshow("image", image)
    # 图像归一化，且转换为浮点型
    fImg = image.astype(np.float32)
    fImg = fImg / 255.0
    # 颜色空间转换 BGR转为HLS
    hlsImg = cv2.cvtColor(fImg, cv2.COLOR_BGR2HLS)
    l = 100
    s = 100
    MAX_VALUE = 100
    # 调节饱和度和亮度的窗口
    cv2.namedWindow("l and s", cv2.WINDOW_AUTOSIZE)
    def nothing(*arg):
        pass
    # 滑动块
    cv2.createTrackbar("l", "l and s", l, MAX_VALUE, nothing)
    cv2.createTrackbar("s", "l and s", s, MAX_VALUE, nothing)
    # 调整饱和度和亮度后的效果
    lsImg = np.zeros(image.shape, np.float32)
    # 调整饱和度和亮度
    while True:
        # 复制
        hlsCopy = np.copy(hlsImg)
        # 得到 l 和 s 的值
        l = cv2.getTrackbarPos('l', 'l and s')
        s = cv2.getTrackbarPos('s', 'l and s')
        # 1.调整亮度（线性变换) , 2.将hlsCopy[:, :, 1]和hlsCopy[:, :, 2]中大于1的全部截取
        hlsCopy[:, :, 1] = (1.0 + l / float(MAX_VALUE)) * hlsCopy[:, :, 1]
        hlsCopy[:, :, 1][hlsCopy[:, :, 1] > 1] = 1
        # 饱和度
        hlsCopy[:, :, 2] = (1.0 + s / float(MAX_VALUE)) * hlsCopy[:, :, 2]
        hlsCopy[:, :, 2][hlsCopy[:, :, 2] > 1] = 1
        # HLS2BGR
        lsImg = cv2.cvtColor(hlsCopy, cv2.COLOR_HLS2BGR)
        # 显示调整后的效果
        cv2.imshow("l and s", lsImg)

        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
            lsImg = lsImg * 255
            lsImg = lsImg.astype(np.uint8)
            cv2.imwrite("lsImg.jpg", lsImg)
            break

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


if __name__ == "__main__":
    main()