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    Python图像处理PIL库的操作总结

    爱喝马黛茶的安东尼爱喝马黛茶的安东尼2019-10-10 17:48:08转载3023

    Matlab确实是一个强大的图像处理工具，不过对于一些简单的图像处理，如图像增强、图像锐化等等，调用python的第三方包PIL(Python Image Library)也可以解决问题，这里把python调用PIL做一些简单的图像处理操作总结下。

    主要用到PIL库里的三个模块：Image、ImageDraw、ImageEnhance。

    1.调整图像大小

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    import Image

    img = Image.open("1.jpg")

    new_img = img.resize((128,128),Image.BILINEAR)

    new_img.save("new_img.jpg")

    将1.jpg的大小转为128*128，Image.BILINEAR 指定采用双线性法对像素点插值。

    两幅图对比(左：原图 右：resize后)

    2.旋转图像

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    import Image

    img = Image.open("1.jpg")

    rot_img = img.rotate(45)

    rot_img.save("rot_img.jpg")

    把图像旋转45度。

    旋转45度

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    3.格式转换

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    rot_img.save("con_img.bmp")

    要把上面生成的 rot_img.jpg 转换成 bmp 图像，加这一行即可。如果不指定保存格式，PIL 将自动根据文件名后缀完成格式之间的转换。

    4.统计直方图

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    import Image

    img = Image.open("1.jpg")

    new_img = img.resize((128,128),Image.BILINEAR)

    rot_img = new_img.rotate(45)

    print (rot_img.histogram())

    Image 类实例的 histogram()方法能够对直方图数据进行统计，并将结果做为一个列表(list)返回,将打印出所有 256 个灰度级像素点个数的统计值：

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    [2812, 7, 18, 18, 16, 25, 18, 22, 27, 41, 24, 34, 24, 22, 23, 20, 33, 32, 22, 20, 22, 21, 21, 24, 21, 27, 3, 8, 19,

    18, 16, 14, 11, 12, 18, 17, 12, 7, 10, 13, 12, 14, 12, 11, 10, 20, 15, 6, 17, 15, 19, 7, 12, 11, 14, 11, 17, 10, 13,

    8, 9, 10, 9, 10, 12, 8, 10, 12, 16, 7, 15, 6, 6, 15, 8, 11, 9, 10, 8, 11, 6, 8, 12, 7, 10, 16, 16, 7, 13, 5, 15, 15,

    13, 8, 8, 13, 10, 19, 9, 13, 11, 8, 7, 18, 17, 9, 13, 10, 16, 22, 7, 17, 8, 14, 10, 11, 5, 13, 9, 17, 14, 14, 16, 15,

    8, 22, 10, 16, 13, 12, 6, 5, 15, 9, 14, 9, 12, 8, 11, 9, 8, 7, 9, 16, 12, 9, 7, 14, 7, 6, 11, 16, 18, 10, 3, 16, 10,

    14, 14, 14, 11, 9, 11, 12, 16, 11, 15, 9, 10, 5, 8, 8, 12, 11, 7, 15, 8, 20, 8, 9, 11, 14, 7, 19, 13, 9, 13, 7, 8, 8,

    16, 20, 2, 16, 6, 13, 8, 11, 14, 14, 9, 14, 8, 14, 15, 14, 8, 14, 25, 14, 16, 21, 12, 10, 12, 17, 21, 15, 12, 34, 16,

    18, 32, 34, 25, 33, 34, 37, 53, 60, 85, 97, 76, 90, 150, 155, 156, 186, 142, 188, 205, 178, 231, 203, 217, 214, 193,

    342, 218, 218, 272, 439, 935, 429, 2787, 1935, 2812, 7, 29, 14, 13, 22, 19, 30, 33, 31, 30, 42, 24, 17, 22, 24, 23,

    37, 18, 19, 21, 30, 20, 22, 14, 20, 4, 10, 23, 16, 18, 7, 14, 15, 15, 17, 12, 6, 23, 11, 4, 11, 13, 15, 15, 14, 17,

    6, 19, 12, 19, 11, 13, 7, 12, 15, 12, 10, 11, 10, 2, 13, 11, 8, 17, 6, 15, 13, 11, 5, 9, 12, 10, 16, 16, 10, 6, 5, 6,

    8, 11, 7, 14, 18, 11, 11, 15, 2, 10, 7, 16, 9, 11, 20, 4, 11, 12, 22, 4, 15, 8, 12, 9, 10, 12, 12, 14, 15, 15, 19,

    11, 17, 6, 13, 6, 13, 6, 9, 12, 22, 13, 13, 11, 18, 13, 17, 8, 14, 14, 10, 14, 8, 11, 17, 10, 8, 11, 10, 11, 2, 6,

    15, 4, 11, 17, 13, 12, 10, 3, 7, 17, 10, 12, 9, 11, 13, 11, 15, 14, 5, 8, 14, 8, 18, 15, 10, 8, 13, 16, 5, 10, 9, 10,

    11, 10, 14, 10, 14, 7, 12, 12, 13, 7, 14, 14, 5, 18, 6, 12, 5, 13, 18, 5, 13, 10, 17, 6, 13, 20, 8, 9, 14, 14, 13, 21,

    11, 12, 17, 14, 12, 8, 15, 13, 15, 12, 14, 19, 18, 17, 19, 27, 18, 23, 31, 27, 16, 27, 30, 28, 34, 37, 45, 40, 46,

    64, 60, 83, 87, 113, 109, 127, 153, 192, 187, 233, 315, 362, 346, 359, 392, 920, 776, 514, 2183, 2670, 24, 2812, 1,

    5, 7, 18, 30, 14, 33, 23, 33, 24, 43, 41, 27, 29, 22, 17, 29, 19, 26, 30, 22, 15, 24, 21, 22, 10, 11, 9, 19, 15, 18,

    11, 16, 14, 11, 15, 7, 16, 7, 20, 11, 17, 10, 12, 16, 10, 9, 18, 12, 14, 13, 11, 12, 13, 13, 14, 16, 5, 13, 5, 7, 10,

    10, 11, 15, 9, 18, 8, 12, 9, 9, 8, 9, 5, 13, 15, 7, 12, 8, 14, 4, 7, 10, 12, 22, 15, 9, 11, 5, 11, 8, 11, 14, 12, 9,

    11, 19, 12, 20, 8, 4, 16, 12, 8, 15, 12, 13, 12, 16, 22, 11, 13, 10, 15, 14, 12, 12, 13, 8, 13, 16, 9, 14, 18, 14,

    14, 15, 11, 13, 9, 12, 11, 11, 9, 9, 13, 12, 12, 10, 10, 9, 12, 4, 6, 7, 6, 15, 11, 11, 13, 10, 12, 12, 11, 12, 9,

    15, 13, 9, 16, 9, 12, 14, 13, 9, 14, 13, 7, 7, 14, 7, 13, 6, 17, 9, 13, 10, 8, 13, 13, 6, 19, 9, 14, 9, 14, 10, 7, 9,

    13, 12, 17, 11, 7, 5, 10, 23, 9, 18, 9, 15, 9, 15, 22, 7, 12, 21, 10, 20, 15, 15, 18, 20, 18, 12, 21, 11, 14, 21, 34,

    22, 42, 44, 63, 48, 55, 56, 62, 87, 91, 106, 115, 164, 174, 183, 144, 159, 144, 156, 172, 190, 164, 177, 258, 229,

    259, 243, 217, 288, 179, 846, 326, 316, 3907, 941]

    下面的操作加入 ImageDraw 模块，因为绘图操作是在图像上进行的，因此实例化 Draw 类的时候要把 Image对象 img 通过参数传递给 Draw 类的构造函数。

    5.绘制直线

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    import Image,ImageDraw

    img = Image.open("1.jpg")

    draw = ImageDraw.Draw(img)

    width,height = img.size  # 得到img的大小

    draw.line(((0,0),(width-1,height-1)),fill=255)   # 对角线方向绘制直线

    draw.line(((0,height-1),(width-1,0)),fill=255)

    img.save("cross_line.jpg")

    绘制对角线

    6.绘制圆

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    import Image,ImageDraw

    img = Image.open("1.jpg")

    width,height = img.size

    draw = ImageDraw.Draw(img)

    draw.arc((0,0,width-1,height-1),0,360,fill=255)

    img.save("circle.jpg")

    (0,0,width-1,height-1)指定了所画弧线的界限；0,360 是所画弧线的起始角度和终止角度； fill=255 指定了所画线的颜色。

    绘制圆

    下面的操作加入ImageEnhance 模块，这个模块提供了一个常用的图像增强工具箱。可以用来进行色彩增强、亮度增强、对比度增强、图像尖锐化等等增强操作。所有操作都有相同形式的接口——通过相应类的 enhance 方法实现。

    7.亮度增强

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    import Image,ImageEnhance 

    img = Image.open("1.jpg") 

    brightness = ImageEnhance.Brightness(img) 

    bright_img = brightness.enhance(2.0) 

    bright_img.save("bright.jpg")

    brightness = ImageEnhance.Brightness(img) 这一行把 img 传给 Brightness 类，得到一个 Brightness 类实例；

    bright_img = brightness.enhance(2.0)  这一行调用 brightness 实例的 enhance 方法，传入的参数指定将亮度增强 2 倍；

    两幅图对比(左：原图 右：增强后)

    8.图像锐化

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    import Image,ImageEnhance

    img = Image.open("1.jpg")

    sharpness = ImageEnhance.Sharpness(img)

    sharp_img = sharpness.enhance(7.0)

    sharp_img.save("sharp.jpg")

    两幅图对比(左：原图 右：锐化后)

    9.对比度增强

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    import Image,ImageEnhance

    img = Image.open("1.jpg")

    contrast = ImageEnhance.Contrast(img)

    contrast_img = contrast.enhance(2.0)

    contrast_img.save("contrast.jpg")

    两幅图对比(左：原图 右：增强后)

    专题推荐：python 图像处理 pil 库
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