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Holistic Processing of Color Images Using Novel Quaternion-Valued Wavelets on the Plane: A promising transformative tool [Hypercomplex Signal and Image Processing] 使用平面上新颖的四元值小波对彩色图像进行整体处理:前景广阔的转换工具 [超复杂信号与图像处理]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-03-01 DOI: 10.1109/MSP.2024.3379753
Neil D. Dizon;Jeffrey A. Hogan
Recently, novel quaternion-valued wavelets on the plane were constructed using an optimization approach. These wavelets are compactly supported, smooth, orthonormal, nonseparable, and truly quaternionic. However, they have not been tested in application. In this article, we introduce a methodology for decomposing and reconstructing color images using quaternionic wavelet filters associated to recently developed quaternion-valued wavelets on the plane. We investigate the applicability of this method in the compression, enhancement, segmentation, and denoising of color images. Our results demonstrate these wavelets as promising tools for an end-to-end quaternion processing of color images.
最近,利用优化方法在平面上构建了新的四元数值小波。这些小波具有紧凑支持、平滑、正交、不可分割和真正的四元性。然而,它们尚未经过应用测试。在本文中,我们介绍了一种使用与最近开发的平面四元值小波相关的四元小波滤波器分解和重建彩色图像的方法。我们研究了这种方法在彩色图像的压缩、增强、分割和去噪方面的适用性。我们的研究结果表明,这些小波是对彩色图像进行端到端四元数处理的理想工具。
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引用次数: 0
Hypercomplex Signal and Image Processing: Part 1 [From the Guest Editors] 超复杂信号与图像处理:第 1 部分 [特邀编辑寄语]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-03-01 DOI: 10.1109/MSP.2024.3378129
Nektarios A. Valous;Eckhard Hitzer;Salvatore Vitabile;Swanhild Bernstein;Carlile Lavor;Derek Abbott;Maria Elena Luna-Elizarrarás;Wilder Lopes
Novel computational signal and image analysis methodologies based on feature-rich mathematical/computational frameworks continue to push the limits of the technological envelope, thus providing optimized and efficient solutions. Hypercomplex signal and image processing is a fascinating field that extends conventional methods by using hypercomplex numbers in a unified framework for algebra and geometry. Methodologies that are developed within this field can lead to more effective and powerful ways to analyze signals and images. Processing audio, video, images, and other types of data in the hypercomplex domain allows for more complex and intuitive representations with algebraic properties that can lead to new insights and optimizations. Applications in image processing, signal filtering, and deep learning (just to name a few) have shown that working in the hypercomplex domain can lead to more efficient and robust outcomes. As research in this field progresses and software tools become more widely available, we can expect to see increasingly sophisticated applications in many areas of research, e.g., computer vision, machine learning, and so on.
基于功能丰富的数学/计算框架的新型计算信号和图像分析方法不断突破技术极限,从而提供优化和高效的解决方案。超复数信号和图像处理是一个引人入胜的领域,它通过在代数和几何的统一框架中使用超复数来扩展传统方法。在这一领域中开发的方法可以带来更有效、更强大的信号和图像分析方法。在超复数领域处理音频、视频、图像和其他类型的数据,可以获得更复杂、更直观的表示方法,其代数特性可以带来新的见解和优化。图像处理、信号滤波和深度学习(仅举几例)中的应用表明,在超复杂域中工作可以带来更高效、更稳健的结果。随着该领域研究的不断深入和软件工具的日益普及,我们有望在计算机视觉、机器学习等多个研究领域看到越来越复杂的应用。
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引用次数: 0
IEEE Connecting IEEE 连接
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2024.3382165
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引用次数: 0
IEEE Feedback IEEE 反馈
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2024.3382164
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引用次数: 0
SPS Scholarship Program SPS 奖学金计划
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2024.3382162
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引用次数: 0
Kerala Chapter Receives the 2023 Chapter of the Year Award! [Society News] 喀拉拉邦分会荣获 2023 年度分会奖![学会新闻]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2023.3345108
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
提供从业人员和研究人员感兴趣的社会信息,包括新闻、评论或技术说明。
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引用次数: 0
Bayes’ Rule Using Imprecise Probabilities [Lecture Notes] 使用不精确概率的贝叶斯法则 [讲义]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2023.3335893
Branko Ristic;Alessio Benavoli;Sanjeev Arulampalam
Bayes’ rule, as one of the fundamental concepts of statistical signal processing, provides a way to update our belief about an event based on the arrival of new pieces of evidence. Uncertainty is traditionally modeled by a probability distribution. Prior belief is thus expressed by a prior probability distribution, while the update involves the likelihood function, a probabilistic expression of how likely it is to observe the evidence. It has been argued by many statisticians, however, that a broadening of probability theory is required because one may not always be able to provide a probability for every event, due to the scarcity of training data.
贝叶斯法则是统计信号处理的基本概念之一,它提供了一种根据新证据更新我们对某一事件的信念的方法。不确定性传统上以概率分布为模型。因此,先验概念用先验概率分布来表示,而更新则涉及似然函数,即观察到证据的可能性有多大的概率表达式。然而,许多统计学家认为,需要拓宽概率理论,因为由于训练数据的稀缺性,我们可能无法总是为每个事件提供概率。
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引用次数: 0
2023 IEEE Signal Processing Society Awards [Society News] 2023 年 IEEE 信号处理学会奖 [学会新闻]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2024.3362573
Presents the recipients of IEEE Signal Processing Society awards for 2023.
介绍电气和电子工程师学会信号处理学会 2023 年度获奖者。
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引用次数: 0
IEEE SPS 2023 President-Elect, Members-at-Large, and Regional Directors-at-Large Election Results [Society News] IEEE SPS 2023 当选主席、无任所会员和地区无任所理事选举结果 [学会新闻]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2023.3326886
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
提供从业人员和研究人员感兴趣的社会信息,包括新闻、评论或技术说明。
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引用次数: 0
Long Polynomial Modular Multiplication Using Low-Complexity Number Theoretic Transform [Lecture Notes] 利用低复杂度数论变换的长多项式模块乘法 [讲义]
IF 14.9 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-01-01 DOI: 10.1109/MSP.2024.3368239
Sin-Wei Chiu;Keshab K. Parhi
This tutorial aims to establish connections between polynomial modular multiplication over a ring to circular convolution and the discrete Fourier transform (DFT). The main goal is to extend the well-known theory of the DFT in signal processing (SP) to other applications involving polynomials in a ring, such as homomorphic encryption (HE).
本教程旨在建立环上多项式模乘与环卷积和离散傅里叶变换(DFT)之间的联系。主要目的是将信号处理(SP)中著名的 DFT 理论扩展到涉及环上多项式的其他应用,如同态加密(HE)。
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引用次数: 0
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IEEE Signal Processing Magazine
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