https://www.v2ex.com/t/303711 基于微信显示png图片 缩略图背景为白色，放大后背景图为黑色的Bug

wechat_black_white_png.go

package main

import (
	"image"
	"image/color"
	"image/png"
	_ "image/png"
	"log"
	"os"
)

func main() {
	black_file, ok := os.Open("black.png")
	if ok != nil {
		log.Fatal(ok)
	}
	defer black_file.Close()
	front_file, ok := os.Open("front.png")
	if ok != nil {
		log.Fatal(ok)
	}
	defer front_file.Close()

	resultFile, err := os.Create("result.png")
	if err != nil {
		log.Fatal(err)
	}
	defer resultFile.Close()

	black, format, ok := image.Decode(black_file)
	if ok != nil || format != "png" {
		log.Fatal(ok)
	}
	front, format, ok := image.Decode(front_file)
	if ok != nil || format != "png" {
		log.Fatal(ok)
	}
	if black.Bounds().Size() != front.Bounds().Size() {
		log.Fatal("image size not equal")
	}

	result := image.NewRGBA(image.Rect(0, 0, black.Bounds().Size().X, black.Bounds().Size().Y))
	var alpha, value uint8
	for x := 0; x < black.Bounds().Size().X; x++ {
		for y := 0; y < black.Bounds().Size().Y; y++ {
			frontValue, _, _, _ := front.At(x, y).RGBA()
			blackValue, _, _, _ := black.At(x, y).RGBA()

			frontValue, blackValue = frontValue>>8, blackValue>>8
			if frontValue <= blackValue {
				alpha = 255
				value = uint8(frontValue)

			} else {
				alpha = uint8(255 - frontValue + blackValue)

				value = uint8(float64(blackValue) / (float64(alpha) / 255))
				// 在存在透明通道的时候RGB算法和python不一致
				value = uint8(uint32(alpha) * uint32(value) >> 8)
			}
			result.SetRGBA(x, y, color.RGBA{value, value, value, alpha})
		}
	}
	png.Encode(resultFile, result)

}

wechat_black_white_png.py

#!/usr/bin/env python
#-*- coding: utf-8 -*-
# Author: ficapy
# Create: '9/18/16'


#########################################################
#  将2张灰度图合并成一张,在白底和黑底分部显示不同的部分
#  完美匹配的要求是:对于相同位置白底总比黑底的像素值大
#  方程式如下(其中y为合成后的像素值,α为alpha值,取值范围0-1)
#  白底:   yα + 255(1-α) = 白底像素值
#  黑底:   yα = 黑底像素值
#  从以上就能看出为啥白色的像素值必须必黑底大
#  如何使用PS制作黑白底图片呢,变亮就用柔光那一种,变暗就用正片叠底
#  然后两张图差值,查看直方图,看靠0的多不多
#  ######################################################


from __future__ import division
from math import ceil
from PIL import Image


front = Image.open('front.png')
black = Image.open('black.png')
assert front.size == black.size
target = front.copy()


img_x,img_y = front.size
front_pix = front.load()
black_pix = black.load()
target_pix = target.load()


for i in range(img_x):
    for j in range(img_y):
        front_value = front_pix[i,j][0]
        black_value = black_pix[i,j][0]
        # 0 为全透明 255为不透明
        if front_value <= black_value:
            alpha = 255
            value = front_value
        else:
            alpha = 255 - front_value + black_value
            value = black_value/(alpha/255) if alpha != 0 else black_value
        alpha,value = ceil(alpha),ceil(value)
        target_pix[i,j] = (value,value,value,alpha)

target.save('result.png')
# 测试查看黑白底效果
# test = Image.open('result.png').convert('RGBA')
# black_background = Image.new( 'RGBA', test.size, 'black')
# white_background = Image.new( 'RGBA', test.size, 'white')
# Image.alpha_composite(black_background, test).save('black_result.png')
# Image.alpha_composite(white_background, test).save('white_result.png')