Region-based fractal image compression using deterministic search

The paper introduces a new method based on deterministic search to fractal image compression. In order to find a good region-based partitioning, we propose a deterministic search method for finding the blocks to be merged. For each range, a list of best N domains is maintained. When two ranges are to be merged and their common edge disappears, for the new range the best N domains are selected only from the 2×N domain extension of the two ranges. At each step the edge with minimum collage error increase is deterministically selected and the two corresponding ranges are merged. The process starts with atomic blocks as ranges and ends when the desired number of ranges is achieved. In order to reduce the encoding time, a suboptimal initialization method is also considered. Experimental results prove that our method yields a better rate-distortion curve than the classic quadtree partitioning scheme