使用地图进行对比度增强

Question

所以我尝试了不同的方式来处理当前图像。我有以下图像和图像的后续掩码：

最近有人向我指出了一种方法，例如图像的对比度增强。我已经寻找可能的方法来做到这一点，例如 hsv 拆分和应用掩码，但没有得到我正在寻找的结果。有没有办法增加图像的对比度，使图像中具有显着性的区域更亮，而低显着性的区域不那么亮。例如下图，我想尝试得到相同的结果。我查看了以下Automatic contrast and brightness adjustment of a color photo of a sheet of paper with OpenCV，但在任何事情上都没有太多运气。

Answer 1

这是 Python/OpenCV 中使用强度修改显着图的硬光组合。您可以根据需要调整 rescale_intensity 中的参数。

图片：

显着性：

import cv2
import numpy as np
import skimage.exposure

# read image 1
img12 = cv2.imread('img12.png')
hh, ww = img12.shape[:2]

# read saliency mask as grayscale and resize to same size as img1
mask = cv2.imread('hard_light_mask.png')
mask = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)
mask = cv2.resize(mask, (ww,hh))
mask = cv2.merge([mask,mask,mask])

# adjust mask contrast and brightness
mask = skimage.exposure.rescale_intensity(mask, in_range=(0,255), out_range=(92,192)).astype(np.uint8)
print(mask.dtype)

# threshold mask at mid gray and convert to 3 channels
thresh = cv2.threshold(mask, 128, 255, cv2.THRESH_BINARY)[1]

# do hard light composite of img12 and mask
# see CSS specs at https://www.w3.org/TR/compositing-1/#blendinghardlight
img12f = img12.astype(np.uint8)/255
maskf =  mask.astype(np.uint8)/255
threshf =  thresh.astype(np.uint8)/255
threshf_inv = 1 - threshf
low = 2.0 * img12f * maskf
high = 1 - 2.0 * (1-img12f) * (1-maskf)
result = ( 255 * (low * threshf_inv + high * threshf) ).clip(0, 255).astype(np.uint8)

# save results
cv2.imwrite('img12_reduced_hardlight.png', result)

# show results
cv2.imshow('img12', img12)
cv2.imshow('mask', mask)
cv2.imshow('thresh', thresh)
cv2.imshow('result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()

结果：