Proceedings ArticleDOI
Enhancing Image Denoising Performance through a Family of Algorithms
Reads0
Chats0
TLDR
In this article , a novel approach that combines wavelet thresholding and BM3D (Block-Matching and 3D Filtering) techniques for effective image denoising is proposed.Abstract:
Images are an integral and indispensable aspect of various disciplines, such as medicine, surveillance, and the entertainment industry. However, the quality of images can be severely compromised by the presence of sensor noise, quantization errors, or transmission errors. This research proposes a novel approach that combines wavelet thresholding and BM3D (Block-Matching and 3D Filtering) techniques for effective image denoising.The efficacy of the methodologies is evaluated and compared to cutting-edge denoising techniques, demonstrating superior performance in both quantitative metrics and visual quality. Furthermore, the study delves into the intricate mechanisms underlying the denoising process and the impact of various parameters on the denoising performance, contributing significantly to the field of image denoising. read more
References
More filters
Journal ArticleDOI
De-noising by soft-thresholding
TL;DR: The authors prove two results about this type of estimator that are unprecedented in several ways: with high probability f/spl circ/*/sub n/ is at least as smooth as f, in any of a wide variety of smoothness measures.
Journal ArticleDOI
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
TL;DR: An algorithm based on an enhanced sparse representation in transform domain based on a specially developed collaborative Wiener filtering achieves state-of-the-art denoising performance in terms of both peak signal-to-noise ratio and subjective visual quality.
Journal ArticleDOI
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
TL;DR: Zhang et al. as mentioned in this paper proposed a feed-forward denoising convolutional neural networks (DnCNNs) to handle Gaussian denobling with unknown noise level.
Journal ArticleDOI
Adaptive wavelet thresholding for image denoising and compression
TL;DR: An adaptive, data-driven threshold for image denoising via wavelet soft-thresholding derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution widely used in image processing applications.
Journal ArticleDOI
Generalized Wiener Filtering Computation Techniques
TL;DR: The classical signal processing technique known as Wiener filtering has been extended to the processing of one-and two-dimensional discrete data by digital operations with emphasis on reduction of the computational requirements.