Multi-view image compression for Visual Sensor Network based on Block Compressive Sensing and multi-phase joint decoding

Ebrahim, Mansoor; Chong, Chai Wai

doi:10.1109/iccst.2014.7045174

Cited by 2 publications

(3 citation statements)

References 21 publications

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“…However, in our research, we have used the joint multiphase decoding (JMD) framework for the reconstruction of images that make use of the TV minimization approach and is referred to as BCS-JMD-TV. A brief overview of the scheme is described as follows, the details of the scheme can be referred from [17,18]…”

Section: Proposed Bcs Visual Sensor Platformmentioning

confidence: 99%

“…BCS-JMD-TV [17,18] is a multi-view compression scheme for VSN based on block-based compressive sensing (BCS) and joint multi-phase decoding (JMD). First, images captured by different visual nodes are encoded using BCS to reduce the hardware complexity.…”

Section: Proposed Bcs Visual Sensor Platformmentioning

confidence: 99%

“…In addition, the developed visual node is also capable of capturing images and recording videos. However, this research work is limited to multi-view image scenario, and BCS along with JMD framework [17,18,19,20] is implemented on low power applications (VSN) to evaluate and analyze its performance based on the reconstruction quality and computational complexity of BCS rather than measuring the bandwidth utilization.…”

Section: Introductionmentioning

confidence: 99%

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Block Compressive Sensing (BCS) Based Low Complexity, Energy Efficient Visual Sensor Platform with Joint Multi-Phase Decoder (JMD)

Ebrahim

Chia

Adil

et al. 2019

Sensors

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Devices in a visual sensor network (VSN) are mostly powered by batteries, and in such a network, energy consumption and bandwidth utilization are the most critical issues that need to be taken into consideration. The most suitable solution to such issues is to compress the captured visual data before transmission takes place. Compressive sensing (CS) has emerged as an efficient sampling mechanism for VSN. CS reduces the total amount of data to be processed such that it recreates the signal by using only fewer sampling values than that of the Nyquist rate. However, there are few open issues related to the reconstruction quality and practical implementation of CS. The current studies of CS are more concentrated on hypothetical characteristics with simulated results, rather than on the understanding the potential issues in the practical implementation of CS and its computational validation. In this paper, a low power, low cost, visual sensor platform is developed using an Arduino Due microcontroller board, XBee transmitter, and uCAM-II camera. Block compressive sensing (BCS) is implemented on the developed platform to validate the characteristics of compressive sensing in a real-world scenario. The reconstruction is performed by using the joint multi-phase decoding (JMD) framework. To the best of our knowledge, no such practical implementation using off the shelf components has yet been conducted for CS.

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Section: Proposed Bcs Visual Sensor Platformmentioning

confidence: 99%

Section: Proposed Bcs Visual Sensor Platformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Block Compressive Sensing (BCS) Based Low Complexity, Energy Efficient Visual Sensor Platform with Joint Multi-Phase Decoder (JMD)

Ebrahim

Chia

Adil

et al. 2019

Sensors

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A Performance Comparative Analysis of Block Based Compressive Sensing and Line Based Compressive Sensing

Ebrahim

Adil

Nawaz

2018

Eng. Technol. Appl. Sci. Res.

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Compressive sensing (CS) is an innovative idea that has opened new areas for viable communication of correlated data. In this paper, a comparative performance analysis of two different variants of compressive sensing i.e. block based compressive sensing (BCS) and line based compressive censing (LCS) schemes is performed for natural images. The idea is to evaluate which variant performs better in terms of reconstruction quality and provides easy initial solution. The experimental analysis demonstrates that LCS scheme can enhance the image reconstruction at lower subrates by 0.5 dB to 2.5 dB, when compared to the BCS scheme.

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Multi-view image compression for Visual Sensor Network based on Block Compressive Sensing and multi-phase joint decoding

Cited by 2 publications

References 21 publications

Block Compressive Sensing (BCS) Based Low Complexity, Energy Efficient Visual Sensor Platform with Joint Multi-Phase Decoder (JMD)

Block Compressive Sensing (BCS) Based Low Complexity, Energy Efficient Visual Sensor Platform with Joint Multi-Phase Decoder (JMD)

A Performance Comparative Analysis of Block Based Compressive Sensing and Line Based Compressive Sensing

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