问题
This is source PNG with transparency: http://i.imgur.com/7m0zIBp.png (13.3kB)
- optimized using compresspng.com: http://i.imgur.com/DHUiLuO.png (5.4kB)
- optimized using tinypng.com: http://i.imgur.com/rEE2hzg.png (5.6kB)
- optimized with gulp-imagemin+imagemin-pngquant: http://i.imgur.com/OTqI6lK.png (6.6kB)
As you can see online tools are better than Gulp. Is there a way to improve PNG optimization with Gulp?
Just in case, here's my gulp task:
gulp.task('images', function() {
return gulp.src('frontend/images/*')
.pipe(imagemin({
progressive: true,
use: [pngquant()]
}))
.pipe(gulp.dest('public/images'));
});
回答1:
You can check out what the various algorithms have done by using ImageMagick's identify -verbose tool, like this
identify -verbose com.png > com.txt
identify -verbose tin.png > tin.txt
identify -verbose gulp.png > gulp.txt
and then compare the outputs - I use opendiff on the Mac. You will see this if you compare com.txt (compresspng) versus gulp.txt
and this if you compare tiny (tinypng) versus gulp.txt
The difference is in the number of colours retained - gulp uses 94 colours, compresspng uses 66, and tiny uses 53.
In case you, or anyone else, wishes to compare any other aspects, I am pasting in the 3 outoput files below for reference:
gulp.txt
Image: gulp.png
Format: PNG (Portable Network Graphics)
Mime type: image/png
Class: DirectClass
Geometry: 560x290+0+0
Units: Undefined
Type: PaletteAlpha
Endianess: Undefined
Colorspace: sRGB
Depth: 8-bit
Channel depth:
red: 8-bit
green: 8-bit
blue: 8-bit
alpha: 8-bit
Channel statistics:
Pixels: 162400
Red:
min: 1 (0.00392157)
max: 245 (0.960784)
mean: 110.922 (0.434989)
standard deviation: 104.067 (0.408106)
kurtosis: -1.74946
skewness: 0.208663
entropy: 0.3477
Green:
min: 40 (0.156863)
max: 245 (0.960784)
mean: 124.973 (0.490091)
standard deviation: 61.139 (0.239761)
kurtosis: -1.32326
skewness: 0.222376
entropy: 0.330503
Blue:
min: 113 (0.443137)
max: 244 (0.956863)
mean: 170.131 (0.667179)
standard deviation: 53.7786 (0.210897)
kurtosis: -1.86628
skewness: 0.233095
entropy: 0.346704
Alpha:
min: 0 (0)
max: 255 (1)
mean: 197.075 (0.772845)
standard deviation: 106.443 (0.417423)
kurtosis: -0.298155
skewness: 1.3014
entropy: 0.157855
Image statistics:
Overall:
min: 0 (0)
max: 255 (1)
mean: 115.988 (0.454854)
standard deviation: 84.8383 (0.332699)
kurtosis: -0.730342
skewness: 0.117783
entropy: 0.295691
Alpha: srgba(76,105,113,0) #4C697100
Colors: 94
Histogram:
660: ( 1, 40,117,255) #012875 srgba(1,40,117,1)
8: ( 1, 58,131,255) #013A83 srgba(1,58,131,1)
4: ( 1, 66,138,255) #01428A srgba(1,66,138,1)
6: ( 1, 75,145,255) #014B91 srgba(1,75,145,1)
2: ( 1, 84,152,255) #015498 srgba(1,84,152,1)
4: ( 1, 93,159,255) #015D9F srgba(1,93,159,1)
3: ( 1,102,166,255) #0166A6 srgba(1,102,166,1)
6: ( 1,111,173,255) #016FAD srgba(1,111,173,1)
4: ( 1,119,180,255) #0177B4 srgba(1,119,180,1)
4: ( 1,128,187,255) #0180BB srgba(1,128,187,1)
1: ( 1,137,194,255) #0189C2 srgba(1,137,194,1)
20: ( 1,146,201,255) #0192C9 srgba(1,146,201,1)
5: ( 1,155,208,255) #019BD0 srgba(1,155,208,1)
3: ( 1,163,215,255) #01A3D7 srgba(1,163,215,1)
5: ( 1,172,222,255) #01ACDE srgba(1,172,222,1)
59271: ( 1,181,229,255) #01B5E5 srgba(1,181,229,1)
91: ( 1,181,229,143) #01B5E58F srgba(1,181,229,0.560784)
80: ( 1,181,229,224) #01B5E5E0 srgba(1,181,229,0.878431)
79: ( 1,181,229, 1) #01B5E501 srgba(1,181,229,0.00392157)
66: ( 1,181,229, 64) #01B5E540 srgba(1,181,229,0.25098)
61: ( 1,181,229, 16) #01B5E510 srgba(1,181,229,0.0627451)
54: ( 1,181,229, 36) #01B5E524 srgba(1,181,229,0.141176)
50: ( 1,181,229, 99) #01B5E563 srgba(1,181,229,0.388235)
46: ( 1,181,229,168) #01B5E5A8 srgba(1,181,229,0.658824)
46: ( 1,181,229, 9) #01B5E509 srgba(1,181,229,0.0352941)
45: ( 1,181,229, 4) #01B5E504 srgba(1,181,229,0.0156863)
39: ( 1,181,229,195) #01B5E5C3 srgba(1,181,229,0.764706)
32: ( 1,181,229, 25) #01B5E519 srgba(1,181,229,0.0980392)
30: ( 1,181,229,120) #01B5E578 srgba(1,181,229,0.470588)
29: ( 1,181,229, 80) #01B5E550 srgba(1,181,229,0.313725)
29: ( 1,181,229, 49) #01B5E531 srgba(1,181,229,0.192157)
4: ( 15, 41,118,255) #0F2976 srgba(15,41,118,1)
64: ( 16,185,230,255) #10B9E6 srgba(16,185,230,1)
4: ( 30, 42,119,255) #1E2A77 srgba(30,42,119,1)
40: ( 32,189,231,255) #20BDE7 srgba(32,189,231,1)
3: ( 44, 43,119,255) #2C2B77 srgba(44,43,119,1)
46: ( 47,193,232,255) #2FC1E8 srgba(47,193,232,1)
7: ( 59, 44,120,255) #3B2C78 srgba(59,44,120,1)
281: ( 62,197,233,255) #3EC5E9 srgba(62,197,233,1)
3: ( 73, 45,121,255) #492D79 srgba(73,45,121,1)
35876: ( 76,105,113, 0) #4C697100 srgba(76,105,113,0)
29: ( 77,201,234,255) #4DC9EA srgba(77,201,234,1)
1: ( 88, 46,122,255) #582E7A srgba(88,46,122,1)
39: ( 93,205,235,255) #5DCDEB srgba(93,205,235,1)
5: (102, 47,123,255) #662F7B srgba(102,47,123,1)
24: (108,209,236,255) #6CD1EC srgba(108,209,236,1)
18: (117, 48,124,255) #75307C srgba(117,48,124,1)
267: (123,213,237,255) #7BD5ED srgba(123,213,237,1)
3: (131, 49,124,255) #83317C srgba(131,49,124,1)
27: (138,217,237,255) #8AD9ED srgba(138,217,237,1)
2: (145, 50,125,255) #91327D srgba(145,50,125,1)
28: (154,221,238,255) #9ADDEE srgba(154,221,238,1)
4: (160, 51,126,255) #A0337E srgba(160,51,126,1)
16: (169,225,239,255) #A9E1EF srgba(169,225,239,1)
16: (174, 52,127,255) #AE347F srgba(174,52,127,1)
202: (184,229,240,255) #B8E5F0 srgba(184,229,240,1)
41: (199,233,241,255) #C7E9F1 srgba(199,233,241,1)
2: (203, 54,128,255) #CB3680 srgba(203,54,128,1)
43: (215,237,242,255) #D7EDF2 srgba(215,237,242,1)
2: (216, 55,129,195) #D83781C3 srgba(216,55,129,0.764706)
3: (218, 55,129,255) #DA3781 srgba(218,55,129,1)
49: (230,241,243,255) #E6F1F3 srgba(230,241,243,1)
53788: (232, 56,130,255) #E83882 srgba(232,56,130,1)
77: (232, 56,130, 99) #E8388263 srgba(232,56,130,0.388235)
72: (232, 56,130, 16) #E8388210 srgba(232,56,130,0.0627451)
71: (232, 56,130,143) #E838828F srgba(232,56,130,0.560784)
69: (232, 56,130,224) #E83882E0 srgba(232,56,130,0.878431)
65: (232, 56,130, 64) #E8388240 srgba(232,56,130,0.25098)
62: (232, 56,130,195) #E83882C3 srgba(232,56,130,0.764706)
52: (232, 56,130, 36) #E8388224 srgba(232,56,130,0.141176)
52: (232, 56,130, 4) #E8388204 srgba(232,56,130,0.0156863)
52: (232, 56,130, 1) #E8388201 srgba(232,56,130,0.00392157)
46: (232, 56,130, 9) #E8388209 srgba(232,56,130,0.0352941)
34: (232, 56,130, 80) #E8388250 srgba(232,56,130,0.313725)
33: (232, 56,130,168) #E83882A8 srgba(232,56,130,0.658824)
27: (232, 56,130, 25) #E8388219 srgba(232,56,130,0.0980392)
26: (232, 56,130,120) #E8388278 srgba(232,56,130,0.470588)
22: (232, 56,130, 49) #E8388231 srgba(232,56,130,0.192157)
57: (233, 68,137,255) #E94489 srgba(233,68,137,1)
34: (234, 80,144,255) #EA5090 srgba(234,80,144,1)
62: (234, 91,151,255) #EA5B97 srgba(234,91,151,1)
402: (235,103,159,255) #EB679F srgba(235,103,159,1)
51: (236,115,166,255) #EC73A6 srgba(236,115,166,1)
35: (237,127,173,255) #ED7FAD srgba(237,127,173,1)
34: (238,139,180,255) #EE8BB4 srgba(238,139,180,1)
43: (239,151,187,255) #EF97BB srgba(239,151,187,1)
44: (239,162,194,255) #EFA2C2 srgba(239,162,194,1)
56: (240,174,201,255) #F0AEC9 srgba(240,174,201,1)
38: (241,186,208,255) #F1BAD0 srgba(241,186,208,1)
58: (242,198,216,255) #F2C6D8 srgba(242,198,216,1)
41: (243,210,223,255) #F3D2DF srgba(243,210,223,1)
53: (243,221,230,255) #F3DDE6 srgba(243,221,230,1)
71: (244,233,237,255) #F4E9ED srgba(244,233,237,1)
8841: (245,245,244,255) #F5F5F4 srgba(245,245,244,1)
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: srgba(223,223,223,1)
Matte color: grey74
Transparent color: none
Interlace: None
Intensity: Undefined
Compose: Over
Page geometry: 560x290+0+0
Dispose: Undefined
Iterations: 0
Compression: Zip
Orientation: Undefined
Properties:
date:create: 2015-03-19T10:05:06+00:00
date:modify: 2015-03-19T10:05:06+00:00
png:cHRM: chunk was found (see Chromaticity, above)
png:gAMA: gamma=0.45455 (See Gamma, above)
png:IHDR.bit-depth-orig: 8
png:IHDR.bit_depth: 8
png:IHDR.color-type-orig: 3
png:IHDR.color_type: 3 (Indexed)
png:IHDR.interlace_method: 0 (Not interlaced)
png:IHDR.width,height: 560, 290
png:PLTE.number_colors: 94
png:sRGB: intent=0 (Perceptual Intent)
png:tRNS: chunk was found
signature: 91476421108f784ce82d392aa2e58bc6c8c5991cf6466f5db98809cc16f0f2ca
Artifacts:
filename: gulp.png
verbose: true
Tainted: False
Filesize: 6.63KB
Number pixels: 162K
Pixels per second: 0B
User time: 0.000u
Elapsed time: 0:01.000
Version: ImageMagick 6.9.0-10 Q16 x86_64 2015-03-10 http://www.imagemagick.org
tin.txt
Image: tin.png
Format: PNG (Portable Network Graphics)
Mime type: image/png
Class: DirectClass
Geometry: 560x290+0+0
Units: Undefined
Type: PaletteAlpha
Endianess: Undefined
Colorspace: sRGB
Depth: 8-bit
Channel depth:
red: 8-bit
green: 8-bit
blue: 8-bit
alpha: 8-bit
Channel statistics:
Pixels: 162400
Red:
min: 0 (0)
max: 245 (0.960784)
mean: 94.0738 (0.368917)
standard deviation: 113.927 (0.446772)
kurtosis: -1.82471
skewness: 0.407541
entropy: 0.400756
Green:
min: 0 (0)
max: 245 (0.960784)
mean: 101.679 (0.398739)
standard deviation: 81.0101 (0.317687)
kurtosis: -1.50733
skewness: 0.171586
entropy: 0.386438
Blue:
min: 0 (0)
max: 244 (0.956863)
mean: 145.019 (0.568702)
standard deviation: 89.1803 (0.349727)
kurtosis: -1.06731
skewness: -0.563292
entropy: 0.389441
Alpha:
min: 0 (0)
max: 255 (1)
mean: 197.073 (0.772837)
standard deviation: 106.446 (0.417434)
kurtosis: -0.298278
skewness: 1.30136
entropy: 0.179828
Image statistics:
Overall:
min: 0 (0)
max: 255 (1)
mean: 99.6745 (0.39088)
standard deviation: 98.5213 (0.386358)
kurtosis: -1.37999
skewness: 0.35773
entropy: 0.339116
Alpha: none #00000000
Colors: 53
Histogram:
36007: ( 0, 0, 0, 0) #00000000 none
664: ( 1, 40,117,255) #012875 srgba(1,40,117,1)
12: ( 1, 60,133,255) #013C85 srgba(1,60,133,1)
12: ( 1, 82,151,255) #015297 srgba(1,82,151,1)
17: ( 1,115,177,255) #0173B1 srgba(1,115,177,1)
29: ( 1,149,204,255) #0195CC srgba(1,149,204,1)
59276: ( 1,181,229,255) #01B5E5 srgba(1,181,229,1)
95: ( 1,181,229, 69) #01B5E545 srgba(1,181,229,0.270588)
93: ( 1,181,229, 19) #01B5E513 srgba(1,181,229,0.0745098)
91: ( 1,181,229,143) #01B5E58F srgba(1,181,229,0.560784)
83: ( 1,181,229, 40) #01B5E528 srgba(1,181,229,0.156863)
80: ( 1,181,229,224) #01B5E5E0 srgba(1,181,229,0.878431)
50: ( 1,181,229, 99) #01B5E563 srgba(1,181,229,0.388235)
46: ( 1,181,229,168) #01B5E5A8 srgba(1,181,229,0.658824)
39: ( 1,181,229,195) #01B5E5C3 srgba(1,181,229,0.764706)
30: ( 1,181,229,120) #01B5E578 srgba(1,181,229,0.470588)
64: ( 16,185,230,255) #10B9E6 srgba(16,185,230,1)
7: ( 36, 42,119,255) #242A77 srgba(36,42,119,1)
86: ( 40,191,232,255) #28BFE8 srgba(40,191,232,1)
281: ( 62,197,233,255) #3EC5E9 srgba(62,197,233,1)
11: ( 65, 44,120,255) #412C78 srgba(65,44,120,1)
68: ( 86,204,235,255) #56CCEB srgba(86,204,235,1)
24: (108,209,236,255) #6CD1EC srgba(108,209,236,1)
28: (118, 48,124,255) #76307C srgba(118,48,124,1)
267: (123,213,237,255) #7BD5ED srgba(123,213,237,1)
189: (133,121,180, 6) #8579B406 srgba(133,121,180,0.0235294)
55: (146,219,238,255) #92DBEE srgba(146,219,238,1)
22: (174, 52,127,255) #AE347F srgba(174,52,127,1)
218: (183,229,240,255) #B7E5F0 srgba(183,229,240,1)
84: (208,235,242,255) #D0EBF2 srgba(208,235,242,1)
49: (230,241,243,255) #E6F1F3 srgba(230,241,243,1)
53791: (232, 56,130,255) #E83882 srgba(232,56,130,1)
103: (232, 56,130,104) #E8388268 srgba(232,56,130,0.407843)
99: (232, 56,130, 18) #E8388212 srgba(232,56,130,0.0705882)
87: (232, 56,130, 60) #E838823C srgba(232,56,130,0.235294)
71: (232, 56,130,143) #E838828F srgba(232,56,130,0.560784)
69: (232, 56,130,224) #E83882E0 srgba(232,56,130,0.878431)
64: (232, 56,130,195) #E83882C3 srgba(232,56,130,0.764706)
52: (232, 56,130, 36) #E8388224 srgba(232,56,130,0.141176)
34: (232, 56,130, 80) #E8388250 srgba(232,56,130,0.313725)
33: (232, 56,130,168) #E83882A8 srgba(232,56,130,0.658824)
91: (234, 72,140,255) #EA488C srgba(234,72,140,1)
62: (234, 91,151,255) #EA5B97 srgba(234,91,151,1)
402: (235,103,159,255) #EB679F srgba(235,103,159,1)
51: (236,115,166,255) #EC73A6 srgba(236,115,166,1)
35: (237,127,173,255) #ED7FAD srgba(237,127,173,1)
77: (239,146,184,255) #EF92B8 srgba(239,146,184,1)
44: (239,162,194,255) #EFA2C2 srgba(239,162,194,1)
56: (240,174,201,255) #F0AEC9 srgba(240,174,201,1)
96: (242,194,213,255) #F2C2D5 srgba(242,194,213,1)
94: (243,217,227,255) #F3D9E3 srgba(243,217,227,1)
71: (244,233,237,255) #F4E9ED srgba(244,233,237,1)
8841: (245,245,244,255) #F5F5F4 srgba(245,245,244,1)
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: srgba(223,223,223,1)
Matte color: grey74
Transparent color: none
Interlace: None
Intensity: Undefined
Compose: Over
Page geometry: 560x290+0+0
Dispose: Undefined
Iterations: 0
Compression: Zip
Orientation: Undefined
Properties:
date:create: 2015-03-19T10:04:55+00:00
date:modify: 2015-03-19T10:04:55+00:00
png:IHDR.bit-depth-orig: 8
png:IHDR.bit_depth: 8
png:IHDR.color-type-orig: 3
png:IHDR.color_type: 3 (Indexed)
png:IHDR.interlace_method: 0 (Not interlaced)
png:IHDR.width,height: 560, 290
png:PLTE.number_colors: 53
png:sRGB: intent=0 (Perceptual Intent)
png:tRNS: chunk was found
signature: f7e69fb1d6be1bde229a91d820f0f42330b923a37e28f0fccb181fdd6485c81c
Artifacts:
filename: tin.png
verbose: true
Tainted: False
Filesize: 5.59KB
Number pixels: 162K
Pixels per second: 0B
User time: 0.000u
Elapsed time: 0:01.000
Version: ImageMagick 6.9.0-10 Q16 x86_64 2015-03-10 http://www.imagemagick.org
com.txt
Image: com.png
Format: PNG (Portable Network Graphics)
Mime type: image/png
Class: DirectClass
Geometry: 560x290+0+0
Units: Undefined
Type: PaletteAlpha
Endianess: Undefined
Colorspace: sRGB
Depth: 8-bit
Channel depth:
red: 8-bit
green: 8-bit
blue: 8-bit
alpha: 8-bit
Channel statistics:
Pixels: 162400
Red:
min: 1 (0.00392157)
max: 245 (0.960784)
mean: 110.909 (0.434937)
standard deviation: 104.021 (0.407927)
kurtosis: -1.74831
skewness: 0.209362
entropy: 0.377289
Green:
min: 40 (0.156863)
max: 245 (0.960784)
mean: 124.952 (0.490008)
standard deviation: 61.1171 (0.239675)
kurtosis: -1.32134
skewness: 0.22372
entropy: 0.367959
Blue:
min: 113 (0.443137)
max: 244 (0.956863)
mean: 170.07 (0.66694)
standard deviation: 53.7829 (0.210913)
kurtosis: -1.86532
skewness: 0.235003
entropy: 0.37823
Alpha:
min: 0 (0)
max: 255 (1)
mean: 197.074 (0.772839)
standard deviation: 106.445 (0.417433)
kurtosis: -0.298201
skewness: 1.30139
entropy: 0.169804
Image statistics:
Overall:
min: 0 (0)
max: 255 (1)
mean: 115.964 (0.454761)
standard deviation: 84.8218 (0.332635)
kurtosis: -0.729488
skewness: 0.118667
entropy: 0.32332
Alpha: srgba(76,105,113,0) #4C697100
Colors: 66
Histogram:
664: ( 1, 40,117,255) #012875 srgba(1,40,117,1)
12: ( 1, 60,133,255) #013C85 srgba(1,60,133,1)
12: ( 1, 82,151,255) #015297 srgba(1,82,151,1)
17: ( 1,115,177,255) #0173B1 srgba(1,115,177,1)
29: ( 1,149,204,255) #0195CC srgba(1,149,204,1)
59276: ( 1,181,229,255) #01B5E5 srgba(1,181,229,1)
91: ( 1,181,229,143) #01B5E58F srgba(1,181,229,0.560784)
91: ( 1,181,229, 6) #01B5E506 srgba(1,181,229,0.0235294)
86: ( 1,181,229, 32) #01B5E520 srgba(1,181,229,0.12549)
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date:create: 2015-03-19T10:04:45+00:00
date:modify: 2015-03-19T10:04:45+00:00
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png:IHDR.bit_depth: 8
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png:IHDR.interlace_method: 0 (Not interlaced)
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png:PLTE.number_colors: 66
png:sRGB: intent=0 (Perceptual Intent)
png:tRNS: chunk was found
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Version: ImageMagick 6.9.0-10 Q16 x86_64 2015-03-10 http://www.imagemagick.org
回答2:
I've spend a lot of time implementing and designing compression algorithms, so let me give a partial answer - although it is probably not what you want to hear.
If you read on how the compression of png file format works, f.ex. here, you will find out that it uses Deflate compression along with a predictor. Deflate compression is a lossless compression algorithm - and even though you can implement it with better or worse compression, I would assume that most implementations will produce roughly the same result in terms of compression level. Nowadays most people don't bother implementing deflate anymore, so the compression itself probably won't do you any good.
The way tools like the one you linked work is by mapping RGB colors to indexed colors. If you have only a limited number of colors (say, 256), you can convert your image to an indexed representation and save it again. Less colors means less information to encode, which means that your compression level is going up. If your image uses only a few colors, or if you're willing to loose information, this can be an option.
Knowing what to look for, I think you can do the same trick in just about any image package, which includes such as f.ex. ImageMagick, Gimp. (In Gimp f.ex. you can do image -> mode -> indexed and save again with all options off).
来源：https://stackoverflow.com/questions/28896407/improve-png-optimization-gulp-task