Motion-blurred image restoration in haze weather based on the color line model

IF 2.7 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Signal Processing-Image Communication Pub Date : 2025-05-23 DOI:10.1016/j.image.2025.117352

Jiamin Li, Hongping Hu, Yanping Bai

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引用次数: 0

Abstract

Many dehazing algorithms had been developed for hazy images caused by industrial pollution and hazy weather. However, most of the dehazing algorithms only consider the restoration of images in static scenes and ignore the restoration of hazy images in dynamic scenes. Based on this, this paper proposed an image recovery algorithm based on the color line model for dynamic scenes under hazy weather. The algorithm was divided into two parts: To improve image contrast by image dehazing and to improve image clarity by deblurring the dynamic scene. Firstly, the watershed algorithm was used to divide the image into foreground and background; Secondly, the color line model was used to restore the motion blur of the foreground image; At the same time, the color line model was adopted to dehazing the hazy background image; And finally, the foreground image and the background image were fused. The experimental results were shown that compared with other mainstream dehazing and deblurring algorithms, the recovered image of this paper's algorithm performs well in terms of both color assurance and texture details, and has better evaluation indexes.

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基于颜色线模型的雾霾天气运动模糊图像恢复

针对工业污染和雾霾天气造成的雾霾图像，开发了许多消雾算法。然而，大多数去雾算法只考虑静态场景下图像的恢复，而忽略了动态场景下模糊图像的恢复。在此基础上，提出了一种基于颜色线模型的雾霾天气下动态场景图像恢复算法。该算法分为两部分：通过图像去雾来提高图像对比度，通过动态场景去模糊来提高图像清晰度。首先，利用分水岭算法将图像划分为前景和背景；其次，利用彩色线模型恢复前景图像的运动模糊；同时，采用色线模型对模糊背景图像进行去雾处理；最后对前景图像和背景图像进行融合。实验结果表明，与其他主流去雾去模糊算法相比，本文算法恢复的图像在色彩保证和纹理细节方面都表现良好，具有更好的评价指标。

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来源期刊

Signal Processing-Image Communication 工程技术-工程：电子与电气

CiteScore

8.40

自引率

2.90%

发文量

138

审稿时长

5.2 months

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.