恢复重新捕获的屏幕图像与分而治之策略

IF 7.5 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yujing Sun;Hao Xiong;Siu Ming Yiu
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引用次数: 0

摘要

重新捕获的屏幕图像中的畸变模式是图像缺陷,可以在很大程度上影响图像质量。与其他图像缺陷不同,moir人工制品在尺度、颜色和形状上变化很大。这种模式与图像内容混合在一起,以不同的方式干扰不同尺度的图像特征,使得去除模式成为一项具有挑战性的任务。在本文中,我们提出了一种新的分而治之策略来解决这个问题。在分割阶段,我们创新地将图像分解为不同的层次,并将其分解为结构成分和细节成分。然后在征服阶段,在分割阶段检索到的层的指导下,我们可以独立地恢复粗、细图像分量,大大提高了分解的性能。我们的战略在定量和定性评估方面都优于最先进的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Restoration of Recaptured Screen Images With a Divide and Conquer Strategy
Moiré patterns in recaptured screen images are image defects that can affect image quality to an extreme extent. Different from other image defects, moiré artefacts can vary greatly in scales, colours and shapes. Such moiré patterns mix with image content and disturb image features of different scales in different ways, making moiré pattern removal a challenging task. In this paper, we present a novel divide-and-conquer strategy to solve the problem. In the divide stage, we innovatively decompose images into different layers, as well as into structure components and detail components. Then in the conquer stage, guided by the layers retrieved from the divide stage, we can restore coarse and fine image components independently, which greatly improve the demoiréing performance. Our strategy outperforms state-of-arts in both quantitative and qualitative evaluations.
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来源期刊
CiteScore
11.80
自引率
2.80%
发文量
114
期刊介绍: The IEEE Transactions on Big Data publishes peer-reviewed articles focusing on big data. These articles present innovative research ideas and application results across disciplines, including novel theories, algorithms, and applications. Research areas cover a wide range, such as big data analytics, visualization, curation, management, semantics, infrastructure, standards, performance analysis, intelligence extraction, scientific discovery, security, privacy, and legal issues specific to big data. The journal also prioritizes applications of big data in fields generating massive datasets.
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