如何在 opencv 中合并一张 RGBA 和一张 RGB 图像

Question

我有两张图片。 在一幅图像中，通过以RGBA图像格式编辑通道A ，将白色像素设置为透明（或无色）。 假设这个图像名称是image_rgba.png而另一个图像是image.jpg 。 现在，我想使用以下 python 代码将image_rgba.png图像放在image.jpg的特定位置

import cv2
import numpy as np
import matplotlib.pyplot as plt

image = cv2.imread('image.jpg')
label = cv2.imread('image_rgba.png')
label = cv2.cvtColor(label, cv2.COLOR_BGR2RGBA)

new_image = image.copy()
new_image = cv2.cvtColor(new_image, cv2.COLOR_BGR2RGBA)

new_image[200:290, 300:384, :] = label

当我写这个图像时，无色的image_rgba.png的边缘在 output 图像中设置为白色（下图中绿色框的白色边缘）。

我希望绿色框 label 的白色边缘不显示，而是显示在该像素中的背景图像。 我发现了类似的问题，但它并不能帮助我解决我的问题。 如果有人可以帮助我，我将不胜感激。

Answer 1

这是你如何做到的。 我不是 OpenCV 专家，所以可能有更简单的方法。 代码中的注释解释了它的作用。 总体思路是：

1. 从 PNG 中提取 alpha 通道
2. 提取一块相同大小的背景
3. 阿尔法混合这些
4. 将结果放回后台

import cv2

def alphaMerge(small_foreground, background, top, left):
    """
    Puts a small BGRA picture in front of a larger BGR background.
    :param small_foreground: The overlay image. Must have 4 channels.
    :param background: The background. Must have 3 channels.
    :param top: Y position where to put the overlay.
    :param left: X position where to put the overlay.
    :return: a copy of the background with the overlay added.
    """
    result = background.copy()
    # From everything I read so far, it seems we need the alpha channel separately
    # so let's split the overlay image into its individual channels
    fg_b, fg_g, fg_r, fg_a = cv2.split(small_foreground)
    # Make the range 0...1 instead of 0...255
    fg_a = fg_a / 255.0
    # Multiply the RGB channels with the alpha channel
    label_rgb = cv2.merge([fg_b * fg_a, fg_g * fg_a, fg_r * fg_a])

    # Work on a part of the background only
    height, width = small_foreground.shape[0], small_foreground.shape[1]
    part_of_bg = result[top:top + height, left:left + width, :]
    # Same procedure as before: split the individual channels
    bg_b, bg_g, bg_r = cv2.split(part_of_bg)
    # Merge them back with opposite of the alpha channel
    part_of_bg = cv2.merge([bg_b * (1 - fg_a), bg_g * (1 - fg_a), bg_r * (1 - fg_a)])

    # Add the label and the part of the background
    cv2.add(label_rgb, part_of_bg, part_of_bg)
    # Replace a part of the background
    result[top:top + height, left:left + width, :] = part_of_bg
    return result

background = cv2.imread('image.jpg')
# Read the image "unchanged" to get the alpha channel as well
label = cv2.imread('image_rgba.png', cv2.IMREAD_UNCHANGED)
result = alphaMerge(label, background, 100, 200)
cv2.imshow("result", result)
cv2.waitKey()

我在以下背景下进行了测试：

而这个前景：

结果如 Python 代码所示：