Super fast color transfer between images(图像色彩转换)

Super fast color transfer between images(图像色彩转换)

英文原文

translator：aaron-clark-aic

图像转换算法

1. 步骤一：输入源图像和目标图像，源图像包含有你想要目标图像上展示的色彩空间。

2. 步骤二：将源图像和目标图像都转换为Lab色彩空间。

   source = cv.cvtColor(source, cv.COLOR_BGR2LAB).astype("float32")
   target = cv.cvtColor(target, cv.COLOR_BGR2LAB).astype("float32")
   

3. 步骤三：分割源图像和目标图像的色彩通道。

   (l, a, b) = cv.split(target)
   

4. 步骤四：计算两幅图Lab色彩空间每个通道的均值和标准差。

   # compute the mean and standard deviation of each channel
   (l, a, b) = cv.split(image)
   (lMean, lStd) = (l.mean(), l.std())
   (aMean, aStd) = (a.mean(), a.std())
   (bMean, bStd) = (b.mean(), b.std())
   

5. 步骤五：目标图像减去目标图像的lab每个通道的均值。

   #5 subtract the means from the target image
   (l, a, b) = cv.split(target)
   l -= lMeanTar
   a -= aMeanTar
   b -= bMeanTar
   

6. 步骤六：按照比例混合色彩通道

   #5 subtract the means from the target image
   (l, a, b) = cv.split(target)
   l -= lMeanTar
   a -= aMeanTar
   b -= bMeanTar
   
   #6 scale by the standard deviations
   l = (lStdTar / lStdSrc) * l
   a = (aStdTar / aStdSrc) * a
   b = (bStdTar / bStdSrc) * b
   

7. 步骤七：添加源图像的通道均值到目标图像中

   #5 subtract the means from the target image
   (l, a, b) = cv.split(target)
   l -= lMeanTar
   a -= aMeanTar
   b -= bMeanTar
   
   #6 scale by the standard deviations
   l = (lStdTar / lStdSrc) * l
   a = (aStdTar / aStdSrc) * a
   b = (bStdTar / bStdSrc) * b
   
   #7 add in the source mean
   l += lMeanSrc
   a += aMeanSrc
   b += bMeanSrc
   

8. 步骤八：过滤掉超过[0，255]范围的值

   # clip the pixel intensities to [0, 255] if they fall outside
   # this range
   l = np.clip(l, 0, 255)
   a = np.clip(a, 0, 255)
   b = np.clip(b, 0, 255)
   

9. 步骤九：合并通道

   # merge the channels together and convert back to the RGB color
   # space, being sure to utilize the 8-bit unsigned integer data
   # type
   transfer = cv.merge([l, a, b])
   

10. 步骤十：转换Lab色彩空间到RGB

    # merge the channels together and convert back to the RGB color
    # space, being sure to utilize the 8-bit unsigned integer data
    # type
    transfer = cv.merge([l, a, b])
    transfer = cv.cvtColor(transfer.astype("uint8"), cv.COLOR_LAB2BGR)
    

完整代码

# import the necessary packages
import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt


def color_transfer(source, target):
    # convert the images from the RGB to L*ab* color space, being
    # sure to utilizing the floating point data type (note: OpenCV
    # expects floats to be 32-bit, so use that instead of 64-bit)
    source = cv.cvtColor(source, cv.COLOR_BGR2LAB).astype("float32")
    target = cv.cvtColor(target, cv.COLOR_BGR2LAB).astype("float32")

    # compute color statistics for the source and target images
    (lMeanSrc, lStdSrc, aMeanSrc, aStdSrc, bMeanSrc, bStdSrc) = image_stats(source)
    (lMeanTar, lStdTar, aMeanTar, aStdTar, bMeanTar, bStdTar) = image_stats(target)

    # subtract the means from the target image
    (l, a, b) = cv.split(target)
    l -= lMeanTar
    a -= aMeanTar
    b -= bMeanTar

    # scale by the standard deviations
    l = (lStdTar / lStdSrc) * l
    a = (aStdTar / aStdSrc) * a
    b = (bStdTar / bStdSrc) * b

    # add in the source mean
    l += lMeanSrc
    a += aMeanSrc
    b += bMeanSrc

    # clip the pixel intensities to [0, 255] if they fall outside
    # this range
    l = np.clip(l, 0, 255)
    a = np.clip(a, 0, 255)
    b = np.clip(b, 0, 255)

    # merge the channels together and convert back to the RGB color
    # space, being sure to utilize the 8-bit unsigned integer data
    # type
    transfer = cv.merge([l, a, b])
    transfer = cv.cvtColor(transfer.astype("uint8"), cv.COLOR_LAB2BGR)

    # return the color transferred image
    return transfer

def image_stats(image):
	# compute the mean and standard deviation of each channel
	(l, a, b) = cv.split(image)
	(lMean, lStd) = (l.mean(), l.std())
	(aMean, aStd) = (a.mean(), a.std())
	(bMean, bStd) = (b.mean(), b.std())

	# return the color statistics
	return (lMean, lStd, aMean, aStd, bMean, bStd)

image_source = cv.imread(".././img/source.jpg")
image_target = cv.imread(".././img/target.jpg")

image_transfer = color_transfer(image_source,image_target)

fig = plt.figure()
ax = fig.add_subplot(131)
ax.set_title("source")
ax.imshow(image_source[:,:,[2,1,0]])
ax = fig.add_subplot(132)
ax.set_title("target")
ax.imshow(image_target[:,:,[2,1,0]])
ax = fig.add_subplot(133)
ax.set_title("transfer")
ax.imshow(image_transfer[:,:,[2,1,0]])
plt.show()

cv.waitKey(0)