Abstract
This study proposes a new image de-nosing algorithm based on Non-Subsampled Contourlet Transform (NSCT) domain in multi-Bessel k form model. Firstly, the noisy image is decomposed into a set of multi-scale and multidirectional frequency sub-bands by NSCT, according to BKF model to scale coefficient of intra-scale and inter-scale processing, fully considering correlation of internal and external scale. Lastly, the estimated coefficients are updated according to inverse non-subsampled Contourlet transformation is performed to get de-noised image. Experimental results show that out algorithm better than the other algorithms in peak signal-to-noise ratio, structural similarity and visual quality.
Highlights
Image inevitably by noise pollution in the process of acquisition and transmission, noise have reduced the image resolution
As a result of Contourlet itself does not have translation invariance, so on the basis of the Contourlet appeared the Non-subsampled Contourlet Transform will be used in image de-noising and obtain better effects (Cunha et al, 2006)
BKF model fully considering correlation of internal and external scale, this study will be the Non-subsampled Contourlet transform and multiple BKF model combined, proposed a new image de-nosing algorithm based on Non-Subsampled Contourlet Transform (NSCT) domain in multi-Bessel k form model
Summary
Image inevitably by noise pollution in the process of acquisition and transmission, noise have reduced the image resolution. As a result of Contourlet itself does not have translation invariance, so on the basis of the Contourlet appeared the Non-subsampled Contourlet Transform will be used in image de-noising and obtain better effects (Cunha et al, 2006).
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