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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Veröffentlicht in:IET computer vision Jg. 14; H. 7; S. 471 - 479
Hauptverfasser: Yan, Yijun, Liu, Yiguang, Yang, Mingqiang, Zhao, Huimin, Chai, Yanmei, Ren, Jinchang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 01.10.2020
Wiley
Schlagworte:
camera network applications
cameras
channel bank filters
colour image decomposition
data analysis
decomposition filters
discrete wavelet filtering banks
discrete wavelet transforms
generated filtering bank
generic wavelet‐based image decomposition
hyperspectral image classification
hyperspectral imagery
hyperspectral imaging
image classification
image coding
image compression
image filtering
image reconstruction
image reconstruction framework
image sensors
intelligent sensors
multimodal data acquisition
multimodal data analysis
multimodal data reconstruction
multispectral imagery
optimisation
optimisation process
reconstruction filters
smart camera applications
Special Issue: Computer Vision for Smart Cameras and Camera Networks
unified framework
wavelet‐based coding
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
ISSN:1751-9632, 1751-9640, 1751-9640
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
ISSN:1751-9632
1751-9640
1751-9640
DOI:10.1049/iet-cvi.2019.0780