A High Performance Filter Based on Statistic Methods for Image Processing
Pao-Ta Yu, Yui-Lang Chen, Bae-Muu Chang · 2008
A novel image processing technology, called a high performance filter based on statistic methods for image processing (HPFSM), is proposed in this paper. In the HPFSM system, a high performance image filter is employed for removal of impulse noise based on statistic methods. While detecting noisy pixels, the concept of algorithms is based on the well-known statistic methods, Chebyshevpsilas theorem, and a fuzzy mean process to estimate the dependable interval for each pixel. Subsequently, restoring process for noisy pixels utilizes a novel method by the scope of mean-closure function with a growing window. Experimental results demonstrate that the HPFSM system achieves high performance for image processing and outperforms the existing well-known methods, even if there are many blocks of noisy pixels at the high noise rate of images.