An enhanced fractal image denoising algorithm

Jian Lu, Zhongxing Ye, Yuru Zou and Ruisong Ye

Chaos, Solitons & Fractals, 2008, vol. 38, issue 4, 1054-1064

Abstract: In recent years, there has been a significant development in image denoising using fractal-based method. This paper presents an enhanced fractal predictive denoising algorithm for denoising the images corrupted by an additive white Gaussian noise (AWGN) by using quadratic gray-level function. Meanwhile, a quantization method for the fractal gray-level coefficients of the quadratic function is proposed to strictly guarantee the contractivity requirement of the enhanced fractal coding, and in terms of the quality of the fractal representation measured by PSNR, the enhanced fractal image coding using quadratic gray-level function generally performs better than the standard fractal coding using linear gray-level function. Based on this enhanced fractal coding, the enhanced fractal image denoising is implemented by estimating the fractal gray-level coefficients of the quadratic function of the noiseless image from its noisy observation. Experimental results show that, compared with other standard fractal-based image denoising schemes using linear gray-level function, the enhanced fractal denoising algorithm can improve the quality of the restored image efficiently.

Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:38:y:2008:i:4:p:1054-1064

DOI: 10.1016/j.chaos.2007.06.048

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