Generic wavelet‐based image decomposition and reconstruction framework for multi‐modal data analysis in smart camera applications.

Yan, Yijun; Liu, Yiguang; Yang, Mingqiang; Zhao, Huimin; Chai, Yanmei; Ren, Jinchang

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.

Citation

YAN, Y., LIU, Y., YANG, M., ZHAO, H., CHAI, Y. and REN, J. 2020. Generic wavelet-based image decomposition and reconstruction framework for multi-modal data analysis in smart camera applications. IET computer vision [online], 14(7): computer vision for smart cameras and camera networks, pages 471-479. Available from: https://doi.org/10.1049/iet-cvi.2019.0780

• Journal Article Type: Article
• Acceptance Date: Jul 13, 2020
• Online Publication Date: Oct 14, 2020
• Publication Date: Oct 31, 2020
• Deposit Date: Oct 25, 2021
• Publicly Available Date: Oct 25, 2021
• Journal: IET Computer Vision
• Print ISSN: 1751-9632
• Electronic ISSN: 1751-9640
• Publisher: Institution of Engineering and Technology
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 7
• Pages: 471-479
• DOI: https://doi.org/10.1049/iet-cvi.2019.0780
• Keywords: Cameras; Channel bank filters; Discrete wavelet transforms; Optimisation; Image classification; Image coding; Image reconstruction; Image sensors; Data analysis; Image filtering; Intelligent sensors; Hyperspectral imaging; Image reconstruction framework
• Public URL: https://rgu-repository.worktribe.com/output/1474880