A Universel Noise Réduction Framework for Denoising Digital Images
نویسندگان
چکیده
The trilateral filter is a nonlinear filter which performs averaging without concentrating on smoothing edges. Selection of the filter parameters is an important issue. A spatial nonlinear filter has been implemented based on local neighborhood about a pixel ) , ( y x f to reduce Gaussian and Impulse noise in images. Our approach is to remove universal noise automatically from synthetic images and biomedical images. The results are remarkably well in terms of quantitative measures of signal restoration as well as an image quality. We tested this procedure on synthetic as well as biomedical images. The wavelet thresholding is combined with trilateral filter to form a novel noise reduction framework, which is very efficient in reducing noise in real noisy images. Experimental results with factual data are provided.
منابع مشابه
An Efficient Curvelet Framework for Denoising Images
Wiener filter suppresses noise efficiently. However, it makes the out image blurred. Curvelet preserves the edges of natural images perfectly, but, it produces visual distortion artifacts and fuzzy edges to the restored image, especially in homogeneous regions of images. In this paper, a new image denoising framework based on Curvelet transform and wiener filter is proposed, which can stop nois...
متن کاملA New Shearlet Framework for Image Denoising
Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed. In Bayesshrink method, sharp features are preserved. However, PSNR (Peak Signal-to-Noise Ratio) is considerably low. BLS-GSM generates some discontinuous information during the course of denoising a...
متن کاملImproved Adaptive Median Filter Algorithm for Removing Impulse Noise from Grayscale Images
Digital image is often degraded by many kinds of noise during the process of acquisition and transmission. To make subsequent processing more convenient, it is necessary to decrease the effect of noise. There are many kinds of noises in image, which mainly include salt and pepper noise and Gaussian noise. This paper focuses on median filters to remove the salt and pepper noise. After summarizin...
متن کاملBiomedical Image Denoising Based on Hybrid Optimization Algorithm and Sequential Filters
Background: Nowadays, image de-noising plays a very important role in medical analysis applications and pre-processing step. Many filters were designed for image processing, assuming a specific noise distribution, so the images which are acquired by different medical imaging modalities must be out of the noise. Objectives: This study has focused on the sequence filters which are selected ...
متن کاملStatistical Wavelet-based Image Denoising using Scale Mixture of Normal Distributions with Adaptive Parameter Estimation
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...
متن کامل