Generic wavelet-based image decomposition and reconstruction framework for multi-modal data analysis in smart camera applications
Effective acquisition, analysis and reconstruction of multi-modal data such as colour and multi-/hyper-spectral imagery is crucial in smart camera applications, where wavelet-based coding and compression of images are highly demanded. Many existing discrete wavelet filtering banks have fixed coeffic...
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| Vydané v: | IET computer vision Ročník 14; číslo 7; s. 471 - 479 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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The Institution of Engineering and Technology
01.10.2020
Wiley |
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| ISSN: | 1751-9632, 1751-9640, 1751-9640 |
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| Abstract | Effective acquisition, analysis and reconstruction of multi-modal data such as colour and multi-/hyper-spectral imagery is crucial in smart camera applications, where wavelet-based coding and compression of images are highly demanded. Many existing discrete wavelet filtering banks have fixed coefficients hence their performance is highly dependent on the signal/image being processed. To tackle this problem, a unified framework is proposed in this study, which can produce a series of discrete wavelet filtering banks, where many existing discrete wavelet filtering banks become special cases of the framework. For each generated filtering bank, it consists of two decomposition filters and two reconstruction filters through an optimisation process. The efficacy of the filtering banks produced by the framework has been validated in two case studies, including colour image decomposition and reconstruction, and hyperspectral image classification. Comprehensive experiments have demonstrated the superior performance of the proposed framework, which will benefit the efficacy of smart camera and camera network applications. |
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| AbstractList | Effective acquisition, analysis and reconstruction of multi‐modal data such as colour and multi‐/hyper‐spectral imagery is crucial in smart camera applications, where wavelet‐based coding and compression of images are highly demanded. Many existing discrete wavelet filtering banks have fixed coefficients hence their performance is highly dependent on the signal/image being processed. To tackle this problem, a unified framework is proposed in this study, which can produce a series of discrete wavelet filtering banks, where many existing discrete wavelet filtering banks become special cases of the framework. For each generated filtering bank, it consists of two decomposition filters and two reconstruction filters through an optimisation process. The efficacy of the filtering banks produced by the framework has been validated in two case studies, including colour image decomposition and reconstruction, and hyperspectral image classification. Comprehensive experiments have demonstrated the superior performance of the proposed framework, which will benefit the efficacy of smart camera and camera network applications. |
| Author | Zhao, Huimin Ren, Jinchang Yan, Yijun Liu, Yiguang Chai, Yanmei Yang, Mingqiang |
| Author_xml | – sequence: 1 givenname: Yijun orcidid: 0000-0003-0224-0078 surname: Yan fullname: Yan, Yijun organization: 1Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK – sequence: 2 givenname: Yiguang surname: Liu fullname: Liu, Yiguang organization: 2College of Computer Science, Sichuan University, Chengdu, People's Republic of China – sequence: 3 givenname: Mingqiang surname: Yang fullname: Yang, Mingqiang organization: 3School of Information Science and Engineering, Shandong University, Jinan, People's Republic of China – sequence: 4 givenname: Huimin surname: Zhao fullname: Zhao, Huimin organization: 4School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, People's Republic of China – sequence: 5 givenname: Yanmei surname: Chai fullname: Chai, Yanmei organization: 5School of Information, Central University of Finance and Economics, Beijing, People's Republic of China – sequence: 6 givenname: Jinchang surname: Ren fullname: Ren, Jinchang email: Jinchang.ren@strath.ac.uk organization: 4School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, People's Republic of China |
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| Keywords | multimodal data acquisition decomposition filters image classification image compression colour image decomposition generic wavelet-based image decomposition image filtering camera network applications multispectral imagery cameras multimodal data analysis optimisation hyperspectral image classification channel bank filters image reconstruction framework smart camera applications unified framework data analysis generated filtering bank discrete wavelet transforms hyperspectral imagery image reconstruction reconstruction filters wavelet-based coding image sensors multimodal data reconstruction intelligent sensors discrete wavelet filtering banks image coding hyperspectral imaging optimisation process |
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| Title | Generic wavelet-based image decomposition and reconstruction framework for multi-modal data analysis in smart camera applications |
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