Low memory image stitching and compression for WMSN using strip-based processing

Wai Chong Chia; Li Wern Chew; Li-Minn Ang; Kah Phooi Seng

doi:10.1504/IJSNET.2012.045037

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Low memory image stitching and compression for WMSN using strip-based processing

Journal article

Peer reviewed

Low memory image stitching and compression for WMSN using strip-based processing

Wai Chong Chia, Li Wern Chew, Li-Minn Ang and Kah Phooi Seng

International Journal of Sensor Networks, Vol.11(1), pp.22-32

2012

DOI: https://doi.org/10.1504/IJSNET.2012.045037

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Abstract

WMSNs

wireless multimedia sensor networks

low memory image stirching

image compression

strip-based processing

multiple cameras

wireless sensor networks

WSNs

field of view

overlapping FOV

Due to the limited Field–Of–View (FOV) of a single camera, it is sometimes desired to extend the FOV using multiple cameras. Image stitching is one of the methods that can be used to exploit and remove the redundancy created by the overlapping FOV. However, the memory requirement and the amount of computation for conventional implementation of image stitching are very high. In this paper, this problem is resolved by performing the image stitching and compression in a strip–by–strip manner. First, the stitching parameters are determined by transmitting two reference images to an intermediate node to perform the processing. Then, these parameters are transmitted back to the visual node and stored in there. These parameters will be used to determine the way of stitching the incoming images in a strip–by–strip manner. After the stitching of a strip is done, it can be further compressed using a strip–based compression technique.

Details

Title: Low memory image stitching and compression for WMSN using strip-based processing
Authors: Wai Chong Chia (Author) - University of Nottingham Malaysia Campus
Li Wern Chew (Author) - University of Nottingham Malaysia Campus
Li-Minn Ang (Author) - University of Nottingham Malaysia Campus
Kah Phooi Seng (Author) - University of Nottingham Malaysia Campus
Publication details: International Journal of Sensor Networks, Vol.11(1), pp.22-32
Publisher: Inderscience Publishers
Date published: 2012
DOI: 10.1504/IJSNET.2012.045037
ISSN: 1748-1279; 1748-1287; 1748-1279
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99513893902621
Output Type: Journal article

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