A Fast Fractal Image Compression Algorithm Combined with Graphic Processor Unit

Directed against the characteristics of computational intensity of fractal image compression encoding, a serial-parallel transfer mechanism is built for encoding procedures. By utilizing the properties of single instruction and multithreading execution of compute unified device architecture (CUDA), the parallel computational model of fractal encoding is built on the graphic processor unit(GPU) in order to parallelize the considerably time-consuming serial execution process of searching for the block of best match. The experimental result indicates, the algorithm in this paper shortens the encoding time to the millisecond scale and significantly boosts the execution efficiency of fractal image encoding algorithm while keeping the decoded image in good quality

A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface

Fractal encoding method becomes an effective image compression method because of its high compression ratio and short decompressing time. But one problem of known fractal compression method is its high computational complexity and consequent long compressing time. To address this issue, in this paper, distance clustering in high dimensional sphere surface is applied to speed up the fractal compression method. Firstly, as a preprocessing strategy, an image is divided into blocks, which are mapped on high dimensional sphere surface. Secondly, a novel image matching method is presented based on distance clustering on high dimensional sphere surface. Then, the correctness and effectiveness properties of the mentioned method are analyzed. Finally, experimental results validate the positive performance gain of the method

Advanced Fractal Image Coding Based on the Quadtree

Fractal image coding simply based on quad tree is a unique technique for still image compression. Compared with other image compression methods, fractal image coding has the advantage of higher compression ratio, higher decoding speed and decoded image having nothing to do with the resolution of image. It spends too much time to look for the best matching Ri block on encoding. To improve the encoding speed, we must narrow the search range and improve the search skills to ensure the best match block falls within our range. In this paper, an advanced fractal image compression algorithm based on quad tree is proposed. First, we can improve the construction method of search attractor by constructing directly from the big Di block, so it can save a lot of searching time in encoding. Second, the attractors can be self-constructed, so it is not happened that the attractor is not found in the traditional methods. Experimental result shows that the algorithm makes image coding faster and more efficiency