利用紧框架特征增强焦点测量中的噪声鲁棒性

IF 3.2 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Yan-Ran Li;Junwei Liu;Zhangtao Ye;Lixin Shen;Xiaosheng Zhuang
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引用次数: 0

摘要

焦点测量被广泛用于评估图像清晰度在各个领域,如摄影和计算机视觉。然而,许多现有的焦点测量在平衡噪声鲁棒性和测量能力方面面临挑战。在这封信中,提出了一种称为紧框架特征方差(VTFF)的新颖焦点度量来解决这一挑战。VTFF利用紧框架特征和特征映射中的方差信息的优势,提供了图像焦点的鲁棒性和准确性评估。在合成数据和实际数据上的实验结果表明,该方法在测量能力、噪声鲁棒性和实时性方面优于现有的焦点测量方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Noise Robustness in Focus Measure Using Tight Framelet Features
Focus measures are widely used to assess image clarity in various fields, such as photography and computer vision. However, many existing focus measures face challenges in balancing noise robustness and measurement capability. In this letter, a novel focus measure called Variance of Tight Framelet Feature (VTFF) is proposed to address this challenge. VTFF leverages the advantages of tight framelet features and variance information in feature maps to provide a robust and accurate assessment of image focus. Experimental results on both synthetic and real-world data demonstrate its superior performance compared to recent focus measures in measurement capability, noise robustness, and real-time performance.
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来源期刊
IEEE Signal Processing Letters
IEEE Signal Processing Letters 工程技术-工程:电子与电气
CiteScore
7.40
自引率
12.80%
发文量
339
审稿时长
2.8 months
期刊介绍: The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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