Results 91 to 100 of about 4,539 (201)

Improving the generalization of image denoising via structure‐preserved MLP‐based denoiser and generative diffusion prior

IET Image Processing, Volume 18, Issue 10, Page 2625-2644, 21 August 2024.
To tackle the challenge posed by images with unknown noise distributions that existing image denoising methods find difficult to handle, this paper introduces a two‐stage enhanced denoising approach aimed at improving generalization performance. The proposed method capitalizes on the implicit structural prior of an MLP‐based denoiser and the generative
Jing Wu, Ruilin Xie, Hao Wu, Guowu Yuan
wiley   +1 more source

Image Deblurring and Effect of Wiener, Regularized, Lucky-Richardson, Blind-Deconvolution, Average and Median Filters on Blurred Image and Noisy Image

Tikrit Journal of Engineering Sciences, 2014
In image deblurring, we try to recover the original, sharp image by using a mathematical model of the blurring process. There are several techniques to recover the original image, but they could not recover the image exactly.
Shayma Wail Nourildean Mohammed Ismaeel Khalil
doaj  

Efficient Dark Channel Prior Based Blind Image De-blurring [PDF]

Radioengineering, 2021
Dark channel prior for blind image de-blurring has attained considerable attention in recent past. An interesting observation in blurring process is that the value of dark channel increases after averaging with adjacent high intensity pixels.
J. Ahmad, I. Touqir, A. M. Siddiqui
doaj  

Enhancing image quality prediction with self‐supervised visual masking

Computer Graphics Forum, Volume 43, Issue 2, May 2024.
Abstract Full‐reference image quality metrics (FR‐IQMs) aim to measure the visual differences between a pair of reference and distorted images, with the goal of accurately predicting human judgments. However, existing FR‐IQMs, including traditional ones like PSNR and SSIM and even perceptual ones such as HDR‐VDP, LPIPS, and DISTS, still fall short in ...
U. Çoğalan, M. Bemana, HP. Seidel, K. Myszkowski   +3 more
wiley   +1 more source

Blind Deblurring Using Internal Patch Recurrence [PDF]

, 2014
Recurrence of small image patches across different scales of a natural image has been previously used for solving ill-posed problems (e.g. super- resolution from a single image). In this paper we show how this multi-scale property can also be used for “blind-deblurring”, namely, removal of an unknown blur from a blurry image.
Tomer Michaeli, Michal Irani
openaire   +1 more source

Improving the Neural Segmentation of Blurry Serial SEM Images by Blind Deblurring. [PDF]

Comput Intell Neurosci, 2023
Cheng A, Kang K, Zhu Z, Zhang R, Wang L.
europepmc   +1 more source

Blind Deblurring of Remote-Sensing Single Images Based on Feature Alignment. [PDF]

Sensors (Basel), 2022
Zhu B, Lv Q, Yang Y, Sui X, Zhang Y, Tang Y, Tan Z.   +6 more
europepmc   +1 more source

Recent Progress in Image Deblurring [PDF]

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques.
Tao, D, Wang, R
core  

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring

Sensors, 2017
Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process.
Naixue Xiong, Ryan Wen Liu, Maohan Liang, Di Wu, Zhao Liu, Huisi Wu   +5 more
doaj   +1 more source

Deep Mean-Shift Priors for Image Restoration

, 2017
In this paper we introduce a natural image prior that directly represents a Gaussian-smoothed version of the natural image distribution. We include our prior in a formulation of image restoration as a Bayes estimator that also allows us to solve noise ...
Bigdeli, Siavash Arjomand, Favaro, Paolo, Jin, Meiguang, Zwicker, Matthias   +3 more
core