Example-based Image Compression
Venue
International Conference on Image Processing (ICIP 2010)
Publication Year
2010
Authors
Jing-Yu Cui, Saurabh Mathur, Michele Covell, Vivek Kwatra, Mei Han
BibTeX
Abstract
The current standard image-compression approaches rely on fairly simple
predictions, using either block- or wavelet-based methods. While many more
sophisticated texture-modeling approaches have been proposed, most do not provide a
significant improvement in compression rate over the current standards at a
workable encoding complexity level. We re-examine this area, using example-based
texture prediction. We find that we can provide consistent and significant
improvements over JPEG, reducing the bit rate by more than 20% for many PSNR
levels. These improvements require consideration of the differences between
residual energy and prediction/residual compressibility when selecting a texture
prediction, as well as careful control of the computational complexity in encoding.
