Image fractal coding algorithm based on complex exponent moments and minimum variance

Feixia Yang; Ziliang Ping; Suhua Zhou

doi:10.1117/12.2266703

8 February 2017 Image fractal coding algorithm based on complex exponent moments and minimum variance

Feixia Yang, Ziliang Ping, Suhua Zhou

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Proceedings Volume 10253, 2016 International Conference on Robotics and Machine Vision; 102530A (2017) https://doi.org/10.1117/12.2266703
Event: 2016 International Conference on Robotics and Machine Vision, 2016, Moscow, Russia

Abstract

Image fractal coding possesses very high compression ratio, the main problem is low speed of coding. The algorithm based on Complex Exponent Moments(CEM) and minimum variance is proposed to speed up the fractal coding compression. The definition of CEM and its FFT algorithm are presented, and the multi-distorted invariance of CEM are discussed. The multi-distorted invariance of CEM is fit to the fractal property of an image. The optimal matching pair of range blocks and domain blocks in an image is determined by minimizing the variance of their CEM. Theory analysis and experimental results have proved that the algorithm can dramatically reduce the iteration time and speed up image encoding and decoding process.

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Feixia Yang, Ziliang Ping, and Suhua Zhou "Image fractal coding algorithm based on complex exponent moments and minimum variance", Proc. SPIE 10253, 2016 International Conference on Robotics and Machine Vision, 102530A (8 February 2017); https://doi.org/10.1117/12.2266703

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KEYWORDS

Image compression

Fractal analysis

Computer programming

Reconstruction algorithms

Image processing

Image quality

Algorithms

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