完整的图片去噪代码(python)

robin

#coding:utf-8
import sys,os
from PIL import Image,ImageDraw
#二值判断,如果确认是噪声,用改点的上面一个点的灰度进行替换
#该函数也可以改成RGB判断的,具体看需求如何
def getPixel(image,x,y,G,N):
L = image.getpixel((x,y))
if L > G:
L = True
else:
L = False
nearDots = 0
if L == (image.getpixel((x - 1,y - 1)) > G):
nearDots += 1
if L == (image.getpixel((x - 1,y)) > G):
nearDots += 1
if L == (image.getpixel((x - 1,y + 1)) > G):
nearDots += 1
if L == (image.getpixel((x,y - 1)) > G):
nearDots += 1
if L == (image.getpixel((x,y + 1)) > G):
nearDots += 1
if L == (image.getpixel((x + 1,y - 1)) > G):
nearDots += 1
if L == (image.getpixel((x + 1,y)) > G):
nearDots += 1
if L == (image.getpixel((x + 1,y + 1)) > G):
nearDots += 1
if nearDots < N:
return image.getpixel((x,y-1))
else:
return None
# 降噪
# 根据一个点A的RGB值，与周围的8个点的RBG值比较，设定一个值N（0 <N <8），当A的RGB值与周围8个点的RGB相等数小于N时，此点为噪点
# G: Integer 图像二值化阀值
# N: Integer 降噪率 0 <N <8
# Z: Integer 降噪次数
# 输出
#  0：降噪成功
#  1：降噪失败
def clearNoise(image,G,N,Z):
draw = ImageDraw.Draw(image)
for i in xrange(0,Z):
for x in xrange(1,image.size[0] - 1):
for y in xrange(1,image.size[1] - 1):
color = getPixel(image,x,y,G,N)
if color != None:
draw.point((x,y),color)
#测试代码
def main():
#打开图片
image = Image.open("d:/1.jpg")
#将图片转换成灰度图片
image = image.convert("L")
#去噪,G = 50,N = 4,Z = 4
clearNoise(image,50,4,4)
#保存图片
image.save("d:/result.jpg")

if __name__ == '__main__':
main()