Title :
A new quadtree decomposition reconstruction method
Author :
Knipe, Jason ; Li, Xiaobo
Author_Institution :
Dept. of Comput. Sci., Alberta Univ., Edmonton, Alta., Canada
Abstract :
Many lossy compression algorithms have been proposed that perform well for low bit rates, but are computationally intense. On the other hand, there are many simple algorithms that perform poorly at high compression ratios. An algorithm that incorporates both computational simplicity and acceptable performance at low bit rates would have many potential applications. In wireless communications, for example, where computing power and transmission speed are important factors, the time required to compress and send image data would need to be reduced significantly. A low bit rate compression algorithm that is conceptually simple as well as computationally efficient is presented in this paper. Theoretically, it can be shown to be computationally superior to JPEG in the compression phase, and comparable in the decompression phase. In practice, the quality of the results, as measured by the PSNR, is found to be better than JPEG results at bit rates lower than about 0.2-0.3 bpp depending on the input image
Keywords :
computational complexity; data compression; image coding; image reconstruction; quadtrees; computational complexity; computational simplicity; image compression; lossy compression algorithms; low bit rate compression algorithm; quadtree decomposition reconstruction method; wireless communications; Bit rate; Compression algorithms; Filters; Gray-scale; Image coding; Image reconstruction; PSNR; Potential well; Reconstruction algorithms; Transform coding;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.546850