Results 91 to 100 of about 4,335 (202)
ExposureNet: Mobile camera exposure parameters autonomous control for blur effect prevention
IET Image Processing, Volume 18, Issue 12, Page 3403-3414, 16 October 2024.The ExposureNet project addresses the issue of image blur caused by imbalanced camera exposure settings, by developing an autonomous system for controlling these settings. The system, trained comprehensively, predicts ideal exposure based on the semantic features of a scene, using only shutter speed and ISO as training signals.
Abdelwahed Nahli +6 more
wiley +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
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
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 +3 more
core
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 +3 more
wiley +1 more source
Blind Deblurring via a Novel Recursive Deep CNN Improved by Wavelet Transform
IEEE Access, 2018 Blind image deconvolution is an ill-posed problem, which is mainly addressed by the regularization methods. Wavelet transform is an effective denoising method related to regularized inversion. In this paper, wavelet transform is utilized to decompose and
Chao Min +3 more
doaj +1 more source
Patch-Wise Blind Image Deblurring Via Michelson Channel Prior
IEEE Access, 2019 Motion blur exists in many computer vision tasks, including faces, texts, and low-illumination images etc. It has been proved that Dark Channel Prior (DCP) and Bright Channel Prior (BCP) can both help the image deblurring by enhancing the dark or bright ...
Guoquan Wen +4 more
doaj +1 more source
FPGA-Based Real-Time Deblurring and Enhancement for UAV-Captured Infrared Imagery
Remote SensingIn response to the inherent limitations of uncooled infrared imaging devices and the image degradation caused by UAV (Unmanned Aerial Vehicle) platform motion, resulting in low contrast and blurred details, a novel single-image blind deblurring and ...
Jianghua Cheng +4 more
doaj +1 more source
A Variational Neural Network Based on Algorithm Unfolding for Image Blind Deblurring
Applied SciencesImage blind deblurring is an ill-posed inverse problem in image processing. While deep learning approaches have demonstrated effectiveness, they often lack interpretability and require extensive data.
Shaoqing Gong +5 more
doaj +1 more source
Blind Image Deblurring via Bayesian Estimation Using Expected Loss
IEEE AccessThis paper introduces a new approach to single image blind deblurring via Bayesian estimation using expected loss, diverging from traditional maximum a posteriori (MAP) estimation methods that are limited by the delta kernel problem-a phenomenon where ...
Jinook Lee, Moon Gi Kang
doaj +1 more source