Question

编辑：感谢Howard，我已经在这里更正了代码，现在似乎正在运行。

EDIT2 ：我已更新代码，以包含原定的垂直模糊。生成的样本输出具有各种设置：Blur comparison images.jpg

模糊操作的另一个参考（Java）：Blurring for Beginners

原帖：

我正在尝试学习基本的图像处理，并在python中复制这个简单的Blur method（第二个函数BlurHorizontal，在“Reusing results”下）。我知道PIL中已有模糊功能，但我想自己尝试基本的像素操作。

此功能应采用源图像，然后基于特定半径平均RGB像素值，并将处理后的图像写入新文件。我的问题是我得到了很多具有完全错误的平均值的像素（例如，在某些区域中亮绿线而不是红色）。

如果模糊半径为2，则平均方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”来保持运行总计，减去输出像素（左侧）并添加新的输入像素（窗口右侧）。 Blur method explained here

示例：Blur test image output.jpg

我出错的任何想法？我不确定为什么图像的某些部分会干净地模糊，而其他区域则充满了与周围区域完全无关的颜色。

感谢您的帮助。

固定工作代码（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

我认为你的线路有问题

for rads in range(-radius, radius):

仅运行到radius-1（范围不包括最后一个）。在第二个范围参数中添加一个。

更新：行内还有另一个小问题

if (co-radius-1) > 0:

应该是

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

Answer 2

我稍微修改/重构了你的代码，并认为我会分享。我需要做一些自定义模糊操作：1）处理数据数组，2）只水平包裹而不是垂直包裹。正如TODO所说，我正在考虑进一步重构，因此它可以进行部分像素混合（即0.5）。希望这有助于某人：

def blur_image(image_data, blur_horizontal=True, blur_vertical=True, height=256, width=256, radius=1):
    #TODO: Modify to support partial pixel blending

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

    out_image_data = image_data

    # blur horizontal row by row, and wrap around edges
    if blur_horizontal:
        for row in range(height):
            for column in range(0, width):
                total_red = 0
                total_green = 0
                total_blue = 0

                for rads in range(-radius, radius+1):
                    pixel = (row*width) + ((column+rads) % width)
                    total_red += image_data[pixel][0]/blur_window
                    total_green += image_data[pixel][1]/blur_window
                    total_blue += image_data[pixel][2]/blur_window

                out_image_data[row*width + column] = (total_red, total_green, total_blue, 255)
        image_data = out_image_data

    # blur vertical, but no wrapping
    if blur_vertical:
        for column in range(width):
            for row in range(0, height):
                total_red = 0
                total_green = 0
                total_blue = 0

                blur_window = 0
                for rads in range(-radius, radius+1):
                    if rads in range(0, height):
                        blur_window += 1

                for rads in range(-radius, radius+1):
                    row_mod = row+rads
                    if row_mod in range(0, height):
                        pixel = (row_mod*width) + column
                        total_red += image_data[pixel][0]/blur_window
                        total_green += image_data[pixel][1]/blur_window
                        total_blue += image_data[pixel][2]/blur_window

                out_image_data[row*width + column] = (total_red, total_green, total_blue, 255)
        image_data = out_image_data

    return image_data

当你已经有一个RGBA像素数组的图像时，你可以使用它，然后运行：

image_data = blur_image(image_data, height=height, width=width, radius=2)

im = Image.new('RGB', (width, height))
im.putdata(image_data)

这个python图像模糊功能有什么问题？

2 个答案: