时间:2020-12-27 16:40:16 | 栏目:Python代码 | 点击:次
本文用 Python 实现 PS 图像调整中的亮度调整,具体的算法原理和效果可以参考之前的博客:
https://www.jb51.net/article/164191.htm
import matplotlib.pyplot as plt from skimage import io file_name='D:/Image Processing/PS Algorithm/4.jpg'; img=io.imread(file_name) Increment = -10.0 img = img * 1.0 I = (img[:, :, 0] + img[:, :, 1] + img[:, :, 2])/3.0 + 0.001 mask_1 = I > 128.0 r = img [:, :, 0] g = img [:, :, 1] b = img [:, :, 2] rhs = (r*128.0 - (I - 128.0) * 256.0) / (256.0 - I) ghs = (g*128.0 - (I - 128.0) * 256.0) / (256.0 - I) bhs = (b*128.0 - (I - 128.0) * 256.0) / (256.0 - I) rhs = rhs * mask_1 + (r * 128.0 / I) * (1 - mask_1) ghs = ghs * mask_1 + (g * 128.0 / I) * (1 - mask_1) bhs = bhs * mask_1 + (b * 128.0 / I) * (1 - mask_1) I_new = I + Increment - 128.0 mask_2 = I_new > 0.0 R_new = rhs + (256.0-rhs) * I_new / 128.0 G_new = ghs + (256.0-ghs) * I_new / 128.0 B_new = bhs + (256.0-bhs) * I_new / 128.0 R_new = R_new * mask_2 + (rhs + rhs * I_new/128.0) * (1-mask_2) G_new = G_new * mask_2 + (ghs + ghs * I_new/128.0) * (1-mask_2) B_new = B_new * mask_2 + (bhs + bhs * I_new/128.0) * (1-mask_2) Img_out = img * 1.0 Img_out[:, :, 0] = R_new Img_out[:, :, 1] = G_new Img_out[:, :, 2] = B_new Img_out = Img_out/255.0 # 饱和处理 mask_1 = Img_out < 0 mask_2 = Img_out > 1 Img_out = Img_out * (1-mask_1) Img_out = Img_out * (1-mask_2) + mask_2 plt.figure() plt.imshow(img/255.0) plt.axis('off') plt.figure(2) plt.imshow(Img_out) plt.axis('off') plt.figure(3) plt.imshow(I/255.0, plt.cm.gray) plt.axis('off') plt.show()
总结