ACM Transactions on Information Systems (TOIS)
DCC '97 Proceedings of the Conference on Data Compression
Fast Progressive Wavelet Coding
DCC '99 Proceedings of the Conference on Data Compression
What's Your Sign?: Efficient Sign Coding for Embedded Wavelet Image Coding
DCC '00 Proceedings of the Conference on Data Compression
Lapped Biorthogonal Transforms for Transform Coding with Reduced Blocking and Ringing Artifacts
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
Fast Adaptive Encoder for Bi-Level Images
DCC '01 Proceedings of the Data Compression Conference
Improving Wavelet Compression with Neural Networks
DCC '01 Proceedings of the Data Compression Conference
A Wavelet Coder for Masked Images
DCC '01 Proceedings of the Data Compression Conference
A patch-based structural masking model with an application to compression
Journal on Image and Video Processing - Special issue on patches in vision
Hi-index | 0.00 |
On-line adaptation to nonstationary distributions is essential to good performance in image coding. Fixed-size contexts (with adaptive tables) are also widely used, in conjunction with arithmetic encoders, in state-of-the-art codecs. In contrast, we propose a simple two-dimensional filter that directly outputs the probability distribution function (PDF) estimate necessary to drive an adaptive arithmetic encoder. The filter is isotropic, in the sense that the impact of a previously encoded bit depends only on its value and distance to the bit to be coded. Surprisingly, this simple filter yields results comparable to or better than JPEG2000. It also brings an interesting distinction between on-line and off-line learning, and their relative importance in compression.