opencv - 使用 mogrify 从 jpg 到 png 进行无损转换

Question

我正在尝试使用 mogrify 将 jpg 图像无损转换为 png 图像。为了得到这个结果，我使用了这个命令:

mogrify -format png  test.jpeg

但是检查两个图像是否相同的测试失败了。为了执行测试，我使用了这个 python 脚本:

import cv2

jpg_image = cv2.imread("test.jpeg")
png_image = cv2.imread("test.png")

diff = jpg_image - png_image

cv2.imshow("diff", diff)
cv2.waitKey(0)
cv2.closeAllWindows()

如果两个图像相同，则此脚本的执行会显示一个黑色矩形。

我尝试使用 opencv 进行转换并且它有效。这是我用来通过 opencv 获取结果的 python 脚本:

import cv2

jpg_image = cv2.imread("/home/roberto/Downloads/index.jpeg")
cv2.imwrite("/home/roberto/Downloads/index.png", jpg_image)

正如下面评论中所建议的，我还在 mogrify 和 opencv 生成的 png 文件上运行了 identify -verbose 命令。这些是输出:

修改

Image: index.png24
  Format: PNG (Portable Network Graphics)
  Mime type: image/png
  Class: DirectClass
  Geometry: 276x183+0+0
  Units: Undefined
  Type: TrueColor
  Endianess: Undefined
  Colorspace: sRGB
  Depth: 8-bit
  Channel depth:
    red: 8-bit
    green: 8-bit
    blue: 8-bit
  Channel statistics:
    Pixels: 50508
    Red:
      min: 0 (0)
      max: 153 (0.6)
      mean: 19.2985 (0.0756804)
      standard deviation: 16.1262 (0.06324)
      kurtosis: 4.912
      skewness: 1.86378
      entropy: 0.805148
    Green:
      min: 0 (0)
      max: 176 (0.690196)
      mean: 64.9359 (0.254651)
      standard deviation: 45.101 (0.176867)
      kurtosis: -0.895497
      skewness: 0.554883
      entropy: 0.968001
    Blue:
      min: 0 (0)
      max: 255 (1)
      mean: 144.46 (0.566511)
      standard deviation: 50.6283 (0.198542)
      kurtosis: -0.289594
      skewness: -0.566585
      entropy: 0.950031
  Image statistics:
    Overall:
      min: 0 (0)
      max: 255 (1)
      mean: 76.2316 (0.298948)
      standard deviation: 40.2384 (0.157798)
      kurtosis: 11.4068
      skewness: 2.70212
      entropy: 0.907726
  Rendering intent: Perceptual
  Gamma: 0.45455
  Chromaticity:
    red primary: (0.64,0.33)
    green primary: (0.3,0.6)
    blue primary: (0.15,0.06)
    white point: (0.3127,0.329)
  Background color: white
  Border color: srgb(223,223,223)
  Matte color: grey74
  Transparent color: black
  Interlace: None
  Intensity: Undefined
  Compose: Over
  Page geometry: 276x183+0+0
  Dispose: Undefined
  Iterations: 0
  Compression: Zip
  Orientation: Undefined
  Properties:
    date:create: 2019-03-21T09:51:42+01:00
    date:modify: 2019-03-21T09:51:42+01:00
    png:bKGD: chunk was found (see Background color, above)
    png:cHRM: chunk was found (see Chromaticity, above)
    png:gAMA: gamma=0.45454544 (See Gamma, above)
    png:IHDR.bit-depth-orig: 8
    png:IHDR.bit_depth: 8
    png:IHDR.color-type-orig: 2
    png:IHDR.color_type: 2 (Truecolor)
    png:IHDR.interlace_method: 0 (Not interlaced)
    png:IHDR.width,height: 276, 183
    png:sRGB: intent=0 (Perceptual Intent)
    png:text: 2 tEXt/zTXt/iTXt chunks were found
    signature: 1bdb735da64a7036eb46f2d257997fbd10044ddc633c2aea5703f1887614709c
  Artifacts:
    filename: index-mogrify.png
    verbose: true
  Tainted: False
  Filesize: 79.9KB
  Number pixels: 50.5K
  User time: 0.000u
  Elapsed time: 0:01.000
  Version: ImageMagick 6.9.7-4 Q16 x86_64 20170114 http://www.imagemagick.org

opencv:

Image: index-opencv.png
  Format: PNG (Portable Network Graphics)
  Mime type: image/png
  Class: DirectClass
  Geometry: 276x183+0+0
  Units: Undefined
  Type: TrueColor
  Endianess: Undefined
  Colorspace: sRGB
  Depth: 8-bit
  Channel depth:
    red: 8-bit
    green: 8-bit
    blue: 8-bit
  Channel statistics:
    Pixels: 50508
    Red:
      min: 0 (0)
      max: 153 (0.6)
      mean: 19.299 (0.0756825)
      standard deviation: 16.1246 (0.0632336)
      kurtosis: 4.91164
      skewness: 1.86412
      entropy: 0.80384
    Green:
      min: 0 (0)
      max: 175 (0.686275)
      mean: 64.9195 (0.254586)
      standard deviation: 45.064 (0.176722)
      kurtosis: -0.898132
      skewness: 0.553704
      entropy: 0.968909
    Blue:
      min: 0 (0)
      max: 255 (1)
      mean: 144.561 (0.566908)
      standard deviation: 50.7463 (0.199005)
      kurtosis: -0.296128
      skewness: -0.559014
      entropy: 0.950698
  Image statistics:
    Overall:
      min: 0 (0)
      max: 255 (1)
      mean: 76.26 (0.299059)
      standard deviation: 40.2739 (0.157937)
      kurtosis: 11.4583
      skewness: 2.7144
      entropy: 0.907815
  Rendering intent: Perceptual
  Gamma: 0.454545
  Chromaticity:
    red primary: (0.64,0.33)
    green primary: (0.3,0.6)
    blue primary: (0.15,0.06)
    white point: (0.3127,0.329)
  Background color: white
  Border color: srgb(223,223,223)
  Matte color: grey74
  Transparent color: black
  Interlace: None
  Intensity: Undefined
  Compose: Over
  Page geometry: 276x183+0+0
  Dispose: Undefined
  Iterations: 0
  Compression: Zip
  Orientation: Undefined
  Properties:
    date:create: 2019-03-21T09:50:20+01:00
    date:modify: 2019-03-21T09:50:20+01:00
    png:IHDR.bit-depth-orig: 8
    png:IHDR.bit_depth: 8
    png:IHDR.color-type-orig: 2
    png:IHDR.color_type: 2 (Truecolor)
    png:IHDR.interlace_method: 0 (Not interlaced)
    png:IHDR.width,height: 276, 183
    png:sRGB: intent=0 (Perceptual Intent)
    signature: 217fe60358faf232f04ccc66dd92ec508fbf82b37858f0b954c87372720b88a1
  Artifacts:
    filename: index-opencv.png
    verbose: true
  Tainted: False
  Filesize: 89.3KB
  Number pixels: 50.5K
  User time: 0.000u
  Elapsed time: 0:01.000
  Version: ImageMagick 6.9.7-4 Q16 x86_64 20170114 http://www.imagemagick.org

谁能给我解释一下第一种和第二种方法(mogirfy vs opencv)的区别？

Answer 1

两个图像之间的差异可以忽略不计。我在左侧展示了 ImageMagick 生成的一个，在右侧展示了 OpenCV 生成的一个。

唯一的区别是像素数据中的一小部分。假设使用 ImageMagick 读取有损图像格式(如 JPEG)将在 OpenCV 读取时产生相同的图像是不合理的。该格式本质上是有损的，允许解码器在达到的准确性和做出的权衡方面有一定的自由裁量权。例如，OpenCV 可能有利于绝对速度和性能。 ImageMagick 可能有利于兼容性和准确性。

不要忘记，虽然您只看到像素为 0..255 之间的整数，但它们实际上被转换为 float 、转换为频域、量化、打包和压缩，然后在读取时发生相反的情况。