MSU JPEG 2000 Image Codecs Comparison
MSU Graphics & Media Lab (Video Group)
Take a look at this article on the new site! Follow the link
https://videoprocessing.ai/codecs/jpeg2000-codecs-comparison-2005.html
Project head: Dr. Dmitriy Vatolin
Measuring: Alexey Moskvin
Refinement, translation: Oleg Petrov
Verification: Artem Titarenko
About comparison
Tested codecs:
- JASPER 1.701.0
- ACDSee 7.0
- Leadtools JPEG 2000 Photoshop plug-in 1.0
- Morgan JPEG 2000 toolbox 1.2 rev 0.0
- Lurawave 2.1.10.04
- Kdu_compress 4.5.2
- JPEG 2000 Compressor (Anything 3D) 1.00.000
- Elecard Wavelet 3.0 Beta
- Photoshop CS2 創ative? plug-in 1.6
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:
- Y-PSNR comparison.
- Visual comparison.
- 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
There are samples of images compressed by every codec in PDF with comparison.
Download
See all MSU Video Codecs Comparisons
MSU video codecs comparisons resources:
- Introduction to Video Codecs Comparison
- Lossless Video Codecs Comparison 2004 (October 2004)
- MPEG-4 SP/ASP Video Codecs Comparison (March 2005)
- JPEG 2000 Image Codecs Comparison (September 2005)
- First Annual MPEG-4 AVC/ H.264 Video Codecs Comparison (January 2005)
- Second Annual MPEG-4 AVC/H.264 Video Codec Comparison (December 2005)
- Subjective Comparison of Modern Video Codecs (February 2006)
- MPEG-2 Video Decoders Comparison (May 2006)
- WMP and JPEG2000 Comparison (October 2006)
- Third Annual MPEG-4 AVC/H.264 Comparison (December 2006) (All versions for free!)
- Lossless Video Codecs Comparison 2007 (March 2007)
- Fourth Annual MPEG-4 AVC/H.264 Comparison (December 2007) (All versions for free!)
- Options Analysis of MPEG-4 AVC/H.264 Codec x264 (December 2008)
- Fifth MPEG-4 AVC/H.264 Comparison (May 2009) (All versions for free!)
- Sixth MPEG-4 AVC/H.264 Comparison (May 2010)
- Seventh MPEG-4 AVC/H.264 Comparison (May 2011)
- Eighth MPEG-4 AVC/H.264 Comparison (May 2012)
- Ninth MPEG-4 AVC/H.264 Comparison (Dec 2013)
- Tenth Video Codec Comparison (HEVC) (Oct 2015)
- Eleventh Video Codec Comparison (HEVC) (Aug 2016)
- Twelfth Video Codec Comparison (HEVC) (Aug 2017)
- Thirteen Video Codec Comparison (HEVC) (Aug 2018)
- Fourteen Video Codec Comparison (HEVC) (Sept 2019)
- Cloud Encoding Servoces Comparison 2019 (Dec 2019)
- Fifteen Video Codec Comparison (HEVC) (Dec 2020)
- Sixteen Video Codec Comparison (Dec 2021)
- Seventeen Video Codecs Comparisons (Nov 2022)
- Eighteenth Video Codecs Comparisons (Apr 2025)
- Nineteenth Video Codecs Comparisons (2025)
- Codec Analysis for Companies:
Other resources
Video resources:
Projects on 3D and stereo video processing and analysis
- MSU S3D-video analysis reports
- MSU 3D Devices Testing
- 3D Displays Video Generation
- 3D Displays Video Capturing
- Stereo Video Depth Map Generation
- SAVAM Saliensy-Aware Video Compression & Dataset
- Video Matting Benchmark
- Video Inpainting Benchmark
MSU Video Quality Measurement tools
Programs with different objective and subjective video quality metrics implementation
- MSU Video Quality Measurement Tool - objective metrics for codecs and filters comparison
- MSU Human Perceptual Quality Metric - several metrics for exact visual tests
Objective and subjective quality evaluation
tests for video and image codecs
- MSU Video Codecs Comparison 2025
- MSU Video Codecs Comparison 2023-2024
- MSU Video Codecs Comparison 2022
- MSU Video Codecs Comparison 2021
- MSU Video Codecs Comparison 2020
- MSU Cloud Benchmark 2020
- Cloud Encoding Services Comparison 2019
- HEVC/AV1 Codec Comparison 2019
- HEVC/AV1 Codec Comparison 2018
- HEVC/AV1 Codec Comparison 2017
- HEVC Codec Comparison 2016
- HEVC Codec Comparison 2015
- 9-th MPEG4-AVC/H.264 Comparison
- 8-th MPEG4-AVC/H.264 Comparison
- 7-th MPEG4-AVC/H.264 Comparison
- 6-th MPEG4-AVC/H.264 Comparison
Here are available VirtualDub and AviSynth filters. For a given type of digital video filtration we typically develop a family of different algorithms and implementations. Generally there are also versions optimized for PC and hardware implementations (ASIC/FPGA/DSP). These optimized versions can be licensed to companies. Please contact us for details via video(at)graphics.cs.msu_ru.
- MSU Cartoon Restore
- MSU Noise Estimation
- MSU Frame Rate Conversion
- MSU Image Restoration
- MSU Denoising
- MSU Old Cinema
- MSU Deblocking
- MSU Smart Brightness and Contrast
- MSU Smart Sharpen
- MSU Noise generation
- MSU Noise estimation
- MSU Motion Estimation Information
- MSU Subtitles removal
- MSU Logo removal
- MSU Deflicker
- MSU Field Shift Fixer AviSynth plug-in
- MSU StegoVideo
- MSU Cartoonizer
- MSU SmartDeblocking
- MSU Color Enhancement
- MSU Old Color Restoration
- MSU TV Commercial Detector
- MSU filters FAQ
- MSU filters statistics
We are working with Intel, Samsung, RealNetworks and other companies on adapting our filters other video processing algorithms for specific video streams, applications and hardware like TV-sets, graphics cards, etc. Some of such projects are non-exclusive. Also we have internal researches. Please let us know via video(at)graphics.cs.msu_ru if you are interested in acquiring a license for such filters or making a custom R&D project on video processing, compression, computer vision.
- 3D Displays Video Generation
- 3D Displays Video Capturing
- Stereo Video Depth Map Generation
- Automatic Objects Segmentation
- Semiautomatic Objects Segmentation
- New Frame Rate Conversion
- New Deinterlacer
- MSU-Samsung Deinterlacing Project
- Digital TV Signal Enhancement
- Old Film Recovery
- Tuner TV Restore
- Panorama
- Video2Photo
- SuperResolution
- SuperPrecision
- MSU-Samsung image and video resampling
- MSU-Samsung Frame Rate Conversion
- Motion Phase filter
- Deshaker (video stabilization)
- Film Grain/Degrain filter
- Deblurring filter
- Video Content Search
Different research and development
projects on video codecs
- MSU Lossless Video Codec (Top!)
- MSU Screen Capture Lossless Codec (Top!)
- MSU MPEG-2 Video Codec
- x264 Codec Improvement
Other information
- Crazy gallery (filters screams :)
- License for commercial usage of MSU VideoGroup Public Software (please be careful: some soft like metrics has another license!)
Server size: 8069 files, 1215Mb (Server statistics)
Project updated by
Server Team and
MSU Video Group
Project sponsored by YUVsoft Corp.
Project supported by MSU Graphics & Media Lab