There has been a lot of research work dedicated towards image denoising. However, with the wide spread of image usage in many fields of our lives, it becomes very important to develop new techniques for image denoising. The previous research in image denoising was based on two of the famous techniques in the image denoising named 2-D Dual-tree Complex Wavelet Transform (2D DTCWT) and 2-D Double...

In this work a new version of block-matching and 3D filtering (BM3D) denoising approach introduced by Dabov et al. for denoising the image corrupted by additive white Gassian noise is proposed. The BM3D performs collaborative filtering to the 3D image groups composed by similar image blocks with the fixed hard-thresholding operator. The proposed version of BM3D adopts adaptive block-matching th...

The quality of biomedical image is degraded by many sources of noise such as imperfect instruments, interference from natural phenomena and data acquisition errors. In Ultrasound and MRI images, the image quality is degraded mainly by Speckle noise and Rician noise respectively. Removing noise from biomedical image is still a challenging problem for the biomedical researchers and lots of denois...

This paper presents a novel approach to image denoising using adaptive principal components. Our assumptions are that the image is corrupted by additive white Gaussian noise. The new denoising technique performs well in terms of image visual fidelity, and in terms of PSNR values, the new technique compares very well against some of the most recently published denoising algorithms.

There are many unavoidable noise interferences in image capturing and transmission. In order 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 & pepper noise and Gaussian noise. This paper focuses on the research of the Gaussian noise removal. It introduces many wavelet threshold denoisin...

In this new era of communication the image and video is important as Visual information transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmission is often corrupted with noise. The received image needs processing before it can be used in applications. Image denoising involves the manipulation of the image d...

The main challenge in digital image processing is to remove noise from the original image. This paper reviews the existing denoising algorithms and performs their comparative study. Different noise models including additive and multiplicative types are discussed in the paper.Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise p...

image denoising, co-occurrence matrix, salt and pepper noise, image statistics, universal denoiser This invention is concerned with a method for removing noise (denoising) from gray level images using statistics that model the image textures. The denoising method presented here uses the framework of the general denoising algorithm published in [1]. The algorithm in [1], known as the Discrete Un...

Removal of noise from an image is an extensively studied problem in image processing. Indeed, the recent advent of sophisticated and highly effective denoising algorithms lead some to believe that existing methods are touching the ceiling in terms of noise removal performance. Can we leverage this impressive achievement to treat other tasks in image processing? Recent work has answered this que...