Fractal Image Coding Based on Classified Range Regions

摘要

A fractal image coding scheme using classified range regions is proposed. Two classes of range regions, shade and nonshade, are defined here, A shade range region is encoded by the average gray level, while a nonshade range region is encoded by IFS parameters. To obtain classified range regions, the two-stage block merging scheme is proposed. Each range region is produced by merging primitive square blocks. Shade range regions are obtained at the first stage, and from the rest of primitive blocks nonshade range regions are obtained at the second stage. Furthermore, for increasing the variety of region shape, the 8-directional block merging scheme is defined by extension of the 4-directional scheme. Also, two similar schemes for encoding region shapes, each corresponding to the 4-directional block merging scheme and the 8-directional block merging scheme, are proposed. From the results of simulation by using a test image, it was demonstrated that the variety of region shape allows large shade range regions to be extracted efficiently, and these large shade range regions are more effective in reduction of total amount of codebits with less increase of degradation of reconstructed image quality than large nonshade range regions. The 8-directional merging and coding scheme and the 4-directional scheme reveal almost the same coding performance, which is improved than that of the quad-tree partitioning scheme. Also, these two schemes achieve almost the same reconstructed image quality.