Improved visual information fidelity based on sensitivity characteristics of digital images

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106892

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106892

Title:	Improved visual information fidelity based on sensitivity characteristics of digital images
Authors:	蘇柏齊;Kuo, Tien-Ying;Su, Po-Chyi;Tsai, Cheng-Mou
Contributors:	資訊電機學院資訊工程學系
Keywords:	Image quality assessment;Log-Gabor filter;Visual information fidelity;Visual sensitivity
Date:	2016-10-01
Issue Date:	2026-04-23 13:47:59 (UTC+8)
Publisher:	Academic Press Inc.;Elsevier Inc
Abstract:	摘要： •An image quality index is developed based on the visual information fidelity.•The features are captured by multi‐scale maximal response of the log-Gabor filter.•Spectral residual approach is utilized to emphasize visual attention. Digital images may lose certain information during transmission or transcoding processes. Since the lost information can influence the visual quality perceived by the human eyes, several quality assessment metrics have been proposed. The structural similarity index (SSIM) and visual information fidelity (VIF) are two of the most common methods that take characteristics of the human perceptual system into account. Although many improved metrics based on SSIM have been developed, the methods related to VIF, which outperforms SSIM-based approaches in certain image databases, have rarely been discussed. This research aims at improving VIF to increase the effectiveness and reduce its computational complexity. The enhanced VIF employs the Haar wavelet transform, log-Gabor filter, and spectral residual approach to emphasize the visual sensitivity in image quality assessment. The experimental results demonstrate the superior performance of the proposed method, when compared to various popular or latest assessment indices. 出版者： Elsevier Inc 出版日期： 2016-10 出處： Journal of visual communication and image representation, 2016-10, Vol.40, p.76-84 資源來源： ScienceDirect (Elsevier) Journals 版權： 2016 Elsevier Inc. 識別號： ISSN: 1047-3203 識別號： EISSN: 1095-9076 識別號： DOI: 10.1016/j.jvcir.2016.06.010
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	28	View/Open

社群 sharing

Loading...