MSU JPEG 2000 Image Codecs Comparison

About comparison

Tested codecs:

Download MSU JPEG 2000 Image Codecs Comparison (27 pages in PDF, 2.01 MB)

Nine codecs have been tested on four images with six compression rates, 216 resulting images.

Goal of JPEG 2000 codecs testing

JPEG 2000 is a new format for image compression. It was developed to replace popular JPEG format and has a lot of advantages: higher compression ratios are available, lossless mode, progressive downloads, error correction, etc.. The main goal of this testing was the comparison of compression quality of available JPEG 2000 codecs: is there any significant difference between implementations of this standard?

Main comparison parts:

  1. Y-PSNR comparison.
  2. Visual comparison.
  3. Informal comparison.

PSNR comparison

PSNR is a metric used to compare two pictures: the more per pixel difference between the pictures is the less is PSNR value. So the higher is the codec’s line on the graph the better is the compression quality.

PSNR was measured using MSU Video Quality Measurement Tool.

Y-PSNR is the difference in brightness component. One JPEG codec is also plotted on graphs. On the following graph one can see that JPEG is far behind the JPEG 2000.
Warning: this is only one of eight graphs from our comparison! All of them can be found in the PDF with comparison.

Barbara image, Y-PSNR

Visual codec comparison

In most cases the PSNR value is in accordance with the compression quality. But sometimes this metric does not reflect presence of some important visual artifacts. For example, we can’t estimate the quality of the blurring artifacts compensation performed by some codec using only PSNR metric. Also in some cases it is difficult to say whether 2 dB difference is significant or not.

That is why in addition to PSNR graphs we use visual comparison of images compressed by different codecs.

ACDSee 7.0, 18324 bytes
Photoshop CS2
Photoshop CS2 plug-in 1.6, 18669 bytes

On these images one can easily see that on this test picture Photoshop CS produces more artifacts than ACDSee.
There are samples of images compressed by every codec in PDF with comparison.




10 Mar 2011
See Also
Learning-Based Image Compression Benchmark
The First extensive comparison of Learned Image Compression algorithms
Call for HEVC codecs 2019
Fourteen modern video codec comparison
HEVC Video Codecs Comparison 2018 (Thirteen MSU Video Codec Comparison)
13th MSU video codecs comparison
HEVC Video Codecs Comparison 2017 (Twelfth MSU Video Codec Comparison)
12th MSU video codecs comparison
MSU Video Codec Comparisons (6 test of lossless, MPEG-4 and MPEG-4 AVC)
Call for HEVC codecs 2018
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