Parallelizing a Two-Pass Improved Encoding Scheme for Fractal Image Compression
An improvement scheme, so named the Two-Pass Improved Encoding Scheme (TIES), for the application to image compression through the extension of the existing concept of Fractal Image Compression (FIC), which capitalizes on the self-similarity within a given image to be compressed, is proposed in this paper. We first briefly explore the existing image compression technology based on FIC, before proceeding to establish the concept behind the TIES algorithm. We then devise an effective encoding and decoding algorithm for the implementation of TIES through the consideration of the domain pool of an image, domain block transformation, scaling and intensity variation, range block approximation using linear combinations, and finally the use of an arithmetic compression algorithm to store the final data as close to source entropy as possible. Also, we compare the performance of this implementation of the TIES algorithm against that of FIC under the same conditions. Additionally, due to the long encoding time required by the TIES algorithm, this paper then proceeds to propose a parallelized version of the TIES algorithm and its implementation, before finally concluding with an empirical analysis of the speedup and scalability of the parallelized TIES algorithm.
Fractal Image Compression Parallel Processing Peak Signal-to-Noise Ratio Linear Combination
Ong Ghim Hwee Ching Kin Wah Eugene
School of Computing, National University of Singapore Republic of Singapore
国际会议
杭州
英文
169-174
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）