摘要翻译:
有限长信号的离散小波变换必须对信号边界进行处理。最先进的方法使用特殊的prolog或epilog阶段,以复杂而不灵活的方式处理这些边界。这尤其适用于分解成多个尺度的图像,在JPEG 2000编码系统中是示例性的。在本文中,将现有的方法扩展到使用紧凑流核进行治疗,可能以多尺度的方式进行治疗。本文重点介绍了JPEG2000中采用的CDF5/3小波和对称边界扩展方法。由于我们的工作,每个输入样本只被访问一次,而结果是立即产生的,即没有缓冲。
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英文标题:
《Simple Signal Extension Method for Discrete Wavelet Transform》
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作者:
David Barina, Pavel Zemcik, Michal Kula
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最新提交年份:
2017
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分类信息:
一级分类:Electrical Engineering and Systems Science 电气工程与系统科学
二级分类:Signal Processing 信号处理
分类描述:Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用,包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、(生物)医学、图像、视频和多模态自然和人为信号,包括通信信号和数据。感兴趣的主题包括:统计信号处理、谱估计和系统辨识;滤波器设计;自适应滤波/随机学习;(压缩)采样、传感和变换域方法,包括快速算法;用于机器学习的信号处理和用于信号处理应用的
机器学习;网络与图形信号处理;信号处理中的凸和非凸优化方法;雷达、声纳和传感器阵列波束形成和测向;通信信号处理;低功耗、多核、片上系统信号处理;信息物理系统的传感、通信、分析和优化,如电网和物联网。
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一级分类:Computer Science 计算机科学
二级分类:Other Computer Science 其他计算机科学
分类描述:This is the classification to use for documents that do not fit anywhere else.
这是用于不适合其他任何地方的文档的分类。
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英文摘要:
Discrete wavelet transform of finite-length signals must necessarily handle the signal boundaries. The state-of-the-art approaches treat such boundaries in a complicated and inflexible way, using special prolog or epilog phases. This holds true in particular for images decomposed into a number of scales, exemplary in JPEG 2000 coding system. In this paper, the state-of-the-art approaches are extended to perform the treatment using a compact streaming core, possibly in multi-scale fashion. We present the core focused on CDF 5/3 wavelet and the symmetric border extension method, both employed in the JPEG 2000. As a result of our work, every input sample is visited only once, while the results are produced immediately, i.e. without buffering.
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PDF链接:
https://arxiv.org/pdf/1709.0846