本篇文章為大家展示了利用python如何調(diào)整圖片的亮度,內(nèi)容簡(jiǎn)明扼要并且容易理解,絕對(duì)能使你眼前一亮,通過(guò)這篇文章的詳細(xì)介紹希望你能有所收獲。
實(shí)現(xiàn)代碼
import matplotlib.pyplot as plt from skimage import io file_name='D:/2020121173119242.png' 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 # 飽和處理 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()
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