{"title":"Scene recovery with detail-preserving","authors":"Tingting Wu , Xinru Wang , Jun Liu , Tieyong Zeng","doi":"10.1016/j.image.2025.117266","DOIUrl":null,"url":null,"abstract":"<div><div>Images captured in sandstorms, hazy, snowy or underwater conditions often suffer from poor visibility. This is mainly due to the presence of atmospheric particles that scatter light. Based on the assumption of highly linear correlation between <span><math><msub><mrow><mi>S</mi></mrow><mrow><mi>n</mi><mi>u</mi></mrow></msub></math></span> and the observed intensity <span><math><mi>I</mi></math></span>, we first estimate the scattering map <span><math><mover><mrow><mi>t</mi></mrow><mrow><mo>̃</mo></mrow></mover></math></span> by projecting the input image <span><math><mi>I</mi></math></span> onto the unified spectrum <span><math><msub><mrow><mi>S</mi></mrow><mrow><mi>n</mi><mi>u</mi></mrow></msub></math></span>. We then apply the weighted guided image filter to make the corresponding transmission map <span><math><mi>t</mi></math></span> more accurate so that details and textures of the input image can be better recovered. Since the atmospheric light <span><math><mi>A</mi></math></span> is also critical to the scene recovery, we propose to use the quad-tree subdivision to extract a correct <span><math><mi>A</mi></math></span>. The quantitative and qualitative evaluations are reported in the numerical experiments. Compared with some SOTA methods, the images recovered by our method exhibit better visibility while preserving details.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"134 ","pages":"Article 117266"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing-Image Communication","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092359652500013X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Images captured in sandstorms, hazy, snowy or underwater conditions often suffer from poor visibility. This is mainly due to the presence of atmospheric particles that scatter light. Based on the assumption of highly linear correlation between and the observed intensity , we first estimate the scattering map by projecting the input image onto the unified spectrum . We then apply the weighted guided image filter to make the corresponding transmission map more accurate so that details and textures of the input image can be better recovered. Since the atmospheric light is also critical to the scene recovery, we propose to use the quad-tree subdivision to extract a correct . The quantitative and qualitative evaluations are reported in the numerical experiments. Compared with some SOTA methods, the images recovered by our method exhibit better visibility while preserving details.
期刊介绍:
Signal Processing: Image Communication is an international journal for the development of the theory and practice of image communication. Its primary objectives are the following:
To present a forum for the advancement of theory and practice of image communication.
To stimulate cross-fertilization between areas similar in nature which have traditionally been separated, for example, various aspects of visual communications and information systems.
To contribute to a rapid information exchange between the industrial and academic environments.
The editorial policy and the technical content of the journal are the responsibility of the Editor-in-Chief, the Area Editors and the Advisory Editors. The Journal is self-supporting from subscription income and contains a minimum amount of advertisements. Advertisements are subject to the prior approval of the Editor-in-Chief. The journal welcomes contributions from every country in the world.
Signal Processing: Image Communication publishes articles relating to aspects of the design, implementation and use of image communication systems. The journal features original research work, tutorial and review articles, and accounts of practical developments.
Subjects of interest include image/video coding, 3D video representations and compression, 3D graphics and animation compression, HDTV and 3DTV systems, video adaptation, video over IP, peer-to-peer video networking, interactive visual communication, multi-user video conferencing, wireless video broadcasting and communication, visual surveillance, 2D and 3D image/video quality measures, pre/post processing, video restoration and super-resolution, multi-camera video analysis, motion analysis, content-based image/video indexing and retrieval, face and gesture processing, video synthesis, 2D and 3D image/video acquisition and display technologies, architectures for image/video processing and communication.