among abundant image denoising methods proposed so far, the use of patchbased algorithms have attracted a lot of attention from image processingcommunity. although these methods are very powerful in presentation of highquality results, the impact of human visual system (hvs) is ignored in sole of them.in this paper the human visual geometry is used in preparation of a new method forimage denois...

There are many unavoidable noise interferences in image acquisition and transmission. To make it better for subsequent processing, the noise in the image should be removed in advance. There are many kinds of image noises, mainly including salt and pepper noise and Gaussian noise. This paper focuses on the research of the Gaussian noise removal. It introduces many wavelet threshold denoising alg...

Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the MAP estimator depends on the proposed model for noise-free wavelet coefficients. Thus in the wa...

improving the quality of medical images at pre and post-surgery operations are necessary for beginning and speeding up the recovery process. partial differential equations (pdes)-based models have become a powerful and well known tool in different areas of image processing such as denoising, multiscale image analysis, edge detection and other fields of image processing and computer vision. in t...

This paper proposes a new hybrid method based on Homomorphic filtering and anisotropicdiffusion equations for image denoising. In this method, the Homomorphic filtering extracts the reflectionand illumination components of a noisy image. Then a suitable image denoising method based onanisotropic diffusion is applied to each components with its special user-defined parameters .This hybridscheme ...

The contourlet transform has the benefit of efficiently capturing the oriented geometrical structures of images. In this paper, by incorporating the ideas of Stein’s Unbiased Risk Estimator (SURE) approach in Nonsubsampled Contourlet Transform (NSCT) domain, a new image denoising technique is devised. We utilize the characteristics of NSCT coefficients in high and low subbands and apply SURE sh...

In this paper, a real-time denoising filter based on modelling of stable hybrid models is presented. Thehybrid models are composed of the shearlet filter and the adaptive Wiener filter in different forms.The optimization of various models is accomplished by the genetic algorithm. Next, regarding thesignificant relationship between Optimal models and input images, changing the structure of Optim...

image denoising by block matching and threedimensionaltransform filtering (bm3d) is a two steps state-ofthe-art algorithm that uses the redundancy of similar blocks innoisy image for removing noise. similar blocks which can havesome overlap are found by a block matching method and groupedto make 3-d blocks for 3-d transform filtering. in this paper wepropose a new block grouping algorithm in th...