Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compres...Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compression as a practical method. The long encoding time results from the need to perform a large number of domain-range matches, the total encoding time is the product of the number of matches and the time to perform each match. In order to improve encoding speed, a hybrid method combining features extraction and self-organization network has been provided, which is based on the feature extraction approach the comparison pixels by pixels between the feature of range blocks and domains blocks. The efficiency of the new method was been proved by examples.展开更多
Fractal encoding technique possesses some particular properties which make it as an attractive approach to video sequences compression. In this paper, we propose a novel fractal based encoding method for video signal...Fractal encoding technique possesses some particular properties which make it as an attractive approach to video sequences compression. In this paper, we propose a novel fractal based encoding method for video signals, which, based on Self Transformation Systems( STS ), is combined with Motion Compensation as well as nonlinear transformation. Experiment of results of realtime image sequences show that the proposed method can achieve a very fast encoding speed and acceptable tradeoff between compression ration and decoding quality.展开更多
文摘Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compression as a practical method. The long encoding time results from the need to perform a large number of domain-range matches, the total encoding time is the product of the number of matches and the time to perform each match. In order to improve encoding speed, a hybrid method combining features extraction and self-organization network has been provided, which is based on the feature extraction approach the comparison pixels by pixels between the feature of range blocks and domains blocks. The efficiency of the new method was been proved by examples.
文摘Fractal encoding technique possesses some particular properties which make it as an attractive approach to video sequences compression. In this paper, we propose a novel fractal based encoding method for video signals, which, based on Self Transformation Systems( STS ), is combined with Motion Compensation as well as nonlinear transformation. Experiment of results of realtime image sequences show that the proposed method can achieve a very fast encoding speed and acceptable tradeoff between compression ration and decoding quality.
