我正在尝试使用jpg
将png
图像无损地转换为mogrify
图像。要获得此结果,我使用以下命令:
mogrify -format png test.jpeg
但是,检查两个图像是否相同的测试失败。要执行测试,我使用以下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,则此脚本的执行将显示一个黑色矩形。
我尝试使用opencv
进行转换,并且可以正常工作。这是我用来通过python
获得结果的opencv
脚本:
import cv2
jpg_image = cv2.imread("/home/roberto/Downloads/index.jpeg")
cv2.imwrite("/home/roberto/Downloads/index.png", jpg_image)
如以下注释中所建议,我还对identify -verbose
和png
生成的mogrify
文件运行了opencv
命令。这些是输出:
mogrify
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
有人可以解释一下第一种方法和第二种方法(mogirfy
与opencv
)之间的区别吗?
答案 0 :(得分:1)
两个图像之间的差异可以忽略不计。我显示 ImageMagick 在左侧产生了一个,而 OpenCV 在右侧产生了一个。
唯一的区别是像素数据中的百分比很小。假设通过 OpenCV 读取具有 ImageMagick 的有损图像格式(例如JPEG)会得到相同的图像是不合理的。格式本质上是有损的,并且允许解码器在其实现的准确性和所做出的权衡方面有一定的酌处权。例如, OpenCV 可能偏向绝对速度和性能。 ImageMagick 可能更喜欢兼容性和准确性。
不要忘记,尽管您只看到像素是介于0..255之间的整数,但实际上它们被转换为浮点数,转换为频域,被量化,打包和压缩,然后在读取时发生相反的情况。