python - 这个python图像模糊函数有什么问题？

Question

编辑:感谢霍华德，我已经更正了这里的代码，它现在似乎可以正常工作了。

EDIT2:我更新了代码以包含最初预期的垂直模糊。使用各种设置生成的示例输出:Blur comparison images.jpg

模糊操作的另一个引用 (Java):Blurring for Beginners

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原帖:

我正在尝试学习基本图像处理并复制这个简单的 Blur method (“重用结果”下的第二个函数 BlurHorizo​​ntal)在 python 中。我知道 PIL 中已经有模糊功能，但我想自己尝试一下基本的像素操作。

此函数应获取源图像，然后根据特定半径对 RGB 像素值进行平均，并将处理后的图像写入新文件。我的问题是我得到了很多平均值完全错误的像素(例如，在某些区域，亮绿色线条而不是红色线条)。

模糊半径为 2 时，平均法将以输入像素为中心的 5 个像素的 RGB 值相加。它使用“滑动窗口”来保持总计，减去传出像素(左侧)并添加新的传入像素(窗口右侧)。 Blur method explained here

样本:Blur test image output.jpg

有什么我哪里出错的想法吗？我不确定为什么图像的某些部分清晰地模糊，而其他区域充满了与周围区域完全无关的颜色。

感谢您的帮助。

FIXED WORKING 代码(感谢 Howard)

import Image, numpy, ImageFilter
img = Image.open('testimage.jpg')

imgArr = numpy.asarray(img) # readonly

# blur radius in pixels
radius = 2

# blur window length in pixels
windowLen = radius*2+1

# columns (x) image width in pixels
imgWidth = imgArr.shape[1]

# rows (y) image height in pixels
imgHeight = imgArr.shape[0]

#simple box/window blur
def doblur(imgArr):
    # create array for processed image based on input image dimensions
    imgB = numpy.zeros((imgHeight,imgWidth,3),numpy.uint8)
    imgC = numpy.zeros((imgHeight,imgWidth,3),numpy.uint8)

    # blur horizontal row by row
    for ro in range(imgHeight):
        # RGB color values
        totalR = 0
        totalG = 0
        totalB = 0

        # calculate blurred value of first pixel in each row
        for rads in range(-radius, radius+1):
            if (rads) >= 0 and (rads) <= imgWidth-1:
                totalR += imgArr[ro,rads][0]/windowLen
                totalG += imgArr[ro,rads][1]/windowLen
                totalB += imgArr[ro,rads][2]/windowLen

        imgB[ro,0] = [totalR,totalG,totalB]

        # calculate blurred value of the rest of the row based on
        # unweighted average of surrounding pixels within blur radius
        # using sliding window totals (add incoming, subtract outgoing pixels)
        for co in range(1,imgWidth):
            if (co-radius-1) >= 0:
                totalR -= imgArr[ro,co-radius-1][0]/windowLen
                totalG -= imgArr[ro,co-radius-1][1]/windowLen
                totalB -= imgArr[ro,co-radius-1][2]/windowLen
            if (co+radius) <= imgWidth-1:
                totalR += imgArr[ro,co+radius][0]/windowLen
                totalG += imgArr[ro,co+radius][1]/windowLen
                totalB += imgArr[ro,co+radius][2]/windowLen

            # put average color value into imgB pixel

            imgB[ro,co] = [totalR,totalG,totalB]

    # blur vertical

    for co in range(imgWidth):
        totalR = 0
        totalG = 0
        totalB = 0

        for rads in range(-radius, radius+1):
            if (rads) >= 0 and (rads) <= imgHeight-1:
                totalR += imgB[rads,co][0]/windowLen
                totalG += imgB[rads,co][1]/windowLen
                totalB += imgB[rads,co][2]/windowLen

        imgC[0,co] = [totalR,totalG,totalB]

        for ro in range(1,imgHeight):
            if (ro-radius-1) >= 0:
                totalR -= imgB[ro-radius-1,co][0]/windowLen
                totalG -= imgB[ro-radius-1,co][1]/windowLen
                totalB -= imgB[ro-radius-1,co][2]/windowLen
            if (ro+radius) <= imgHeight-1:
                totalR += imgB[ro+radius,co][0]/windowLen
                totalG += imgB[ro+radius,co][1]/windowLen
                totalB += imgB[ro+radius,co][2]/windowLen

            imgC[ro,co] = [totalR,totalG,totalB]

    return imgC

# number of times to run blur operation
blurPasses = 3

# temporary image array for multiple passes
imgTmp = imgArr

for k in range(blurPasses):
    imgTmp = doblur(imgTmp)
    print "pass #",k,"done."

imgOut = Image.fromarray(numpy.uint8(imgTmp))

imgOut.save('testimage-processed.png', 'PNG')

Answer 1

我想你的线路有问题

for rads in range(-radius, radius):

仅运行到 radius-1(范围不包括最后一个)。将 1 添加到第二个范围参数。

更新:行内还有一个小问题

if (co-radius-1) > 0:

应该是

if (co-radius-1) >= 0: