Region-Based Fractal Compression for Still Image

Abstract

Fractal image coding is a novel and attractive technique for still image compression. By utilizing the characteristic of self-similarity, an iterated function system can automatically converts an image into a set of affine transformation coefficients. However, the conventional block-based segmentation methods inadequately satisfy the natural image property and thus can’t achieve an efficient performance. In this paper, we propose a thorough fractal image compression system to approach the target of very low bit-rate. To more efficiently utilize the property of natural images, an image dependent region-based segmentation technique is proposed. This region-based process consists of two steps: First, we improve the performance of quadtree decomposition by utilizing the adaptive threshold method. Second, a merging scheme is introduced to the result of quadtree decomposition that combines several similar blocks into a small number of regions. We also provide a quadtree-based segmented chain code to efficiently record the contours of the regions. Moreover, a post-processing algorithm is applied according to region-based segmentation to eliminate the blocking artifact. The experimental results indicate that the proposed method has the potential to achieve comparable extreme low bit rate among the existing method at the same level of quality.