完整的图片去噪代码(python)
#coding:utf-8import sys,osfrom 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 - 1): for y in xrange(1,image.size - 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()
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