关键词: 分形图像压缩, Fisher分类, 灰度变换, 内积空间映射, 压缩因子, 四叉树分割

Abstract: Concerning the poor matching performance of two-dimensional gray-scale transformation in Fisher classification algorithm, an improved space mapping gray-scale transformation method was proposed. It put position and brightness into the gray-scale transformation at the same time, and formatted linear mapping between three-dimensional curved surfaces. The method quantified the scaling coefficient firstly, then calculated and quantified the other coefficients of improved gray-scale transformation to improve the possibility of successful range-domain matching. The experimental results show that this method reduces the number of coding blocks, improves the compression ratio and shortens the encoding time, while the quality of decoded image does not get much influenced.

Key words: fractal image compression, Fisher classification, gray-scale transformation, inner product space mapping, scaling coefficient, quadtree partition