MSU Windows Media Photo (Microsoft HD Photo) and JPEG 2000 Codecs Comparison
- Project head: Dr. Dmitriy Vatolin
- Measurements: Alexey Moskvin
- Refinement, translation: Oleg Petrov
About comparison
Tested codecs:
- Windows Media Photo
- 9 codecs from last year’s JPEG 2000 Image Codecs Comparison
Download MSU Windows Media Photo and JPEG 2000 Codecs Comparison (26 pages in PDF, 4833 KB)
Goal of WMPhoto testing
WMPhoto is a new format for image compression that is said to have better quality/compression ratio than that of current standards, including JPEG 2000. The main goal of this testing was the verification of superiority of WMPhoto by comparing it against nine JPEG 2000 codecs from last year’s JPEG 2000 Image Codecs Comparison.
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 the PRO version of MSU Video Quality Measurement Tool (with command line support).
Y-PSNR is the difference in brightness component. There are three graphs
for WMPhoto, they correspond to different values of overlapping
parameter (“l”).
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 artefacts. For example, we can’t estimate the quality of the blurring artefacts compensation performed by some codec using only PSNR metric. Also in some cases it is difficult to say whether 2 dB differens 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 |
 WMPhoto, 16553 bytes |
There are samples of images compressed by every codec in PDF with comparison.
Download
Contacts
E-mail: video@graphics.cs.msu.ru
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MSU Benchmark Collection
- Video Colorization Benchmark
- Super-Resolution for Video Compression Benchmark
- Defenses for Image Quality Metrics Benchmark
- Learning-Based Image Compression Benchmark
- Super-Resolution Quality Metrics Benchmark
- Video Saliency Prediction Benchmark
- Metrics Robustness Benchmark
- Video Upscalers Benchmark
- Video Deblurring Benchmark
- Video Frame Interpolation Benchmark
- HDR Video Reconstruction Benchmark
- No-Reference Video Quality Metrics Benchmark
- Full-Reference Video Quality Metrics Benchmark
- Video Alignment and Retrieval Benchmark
- Mobile Video Codecs Benchmark
- Video Super-Resolution Benchmark
- Shot Boundary Detection Benchmark
- The VideoMatting Project
- Video Completion
- Codecs Comparisons & Optimization
- VQMT
- MSU Datasets Collection
- Metrics Research
- Video Quality Measurement Tool 3D
- Video Filters
- Other Projects