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Proceedings Paper

Performance comparison of leading image codecs: H.264/AVC Intra, JPEG2000, and Microsoft HD Photo
Author(s): Trac D. Tran; Lijie Liu; Pankaj Topiwala
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Paper Abstract

This paper provides a detailed rate-distortion performance comparison between JPEG2000, Microsoft HD Photo, and H.264/AVC High Profile 4:4:4 I-frame coding for high-resolution still images and high-definition (HD) 1080p video sequences. This work is an extension to our previous comparative study published in previous SPIE conferences [1, 2]. Here we further optimize all three codecs for compression performance. Coding simulations are performed on a set of large-format color images captured from mainstream digital cameras and 1080p HD video sequences commonly used for H.264/AVC standardization work. Overall, our experimental results show that all three codecs offer very similar coding performances at the high-quality, high-resolution setting. Differences tend to be data-dependent: JPEG2000 with the wavelet technology tends to be the best performer with smooth spatial data; H.264/AVC High-Profile with advanced spatial prediction modes tends to cope best with more complex visual content; Microsoft HD Photo tends to be the most consistent across the board. For the still-image data sets, JPEG2000 offers the best R-D performance gains (around 0.2 to 1 dB in peak signal-to-noise ratio) over H.264/AVC High-Profile intra coding and Microsoft HD Photo. For the 1080p video data set, all three codecs offer very similar coding performance. As in [1, 2], neither do we consider scalability nor complexity in this study (JPEG2000 is operating in non-scalable, but optimal performance mode).

Paper Details

Date Published: 24 September 2007
PDF: 14 pages
Proc. SPIE 6696, Applications of Digital Image Processing XXX, 66960B (24 September 2007); doi: 10.1117/12.775472
Show Author Affiliations
Trac D. Tran, FastVDO, LLC (United States)
Lijie Liu, FastVDO, LLC (United States)
Pankaj Topiwala, FastVDO, LLC (United States)

Published in SPIE Proceedings Vol. 6696:
Applications of Digital Image Processing XXX
Andrew G. Tescher, Editor(s)

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