A comparative study on image compression method using stand-alone DWT techniques and hybrid of DWT with huffman coding technique for WSN application
The advent of wireless technologies nowadays gives high impact toward many users to communicate to each other. Wireless Sensor Net-work is a network of nodes which connect to each other by using a device. In addition, transmitting and receiving messages and files are common in most users. There are...
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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
WARSE
2002
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Subjects: | |
Online Access: | http://eprints.uthm.edu.my/6335/1/AJ%202020%20%28815%29.pdf http://eprints.uthm.edu.my/6335/ https://doi.org/10.30534/ijatcse/2020/1891.42020 |
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Institution: | Universiti Tun Hussein Onn Malaysia |
Language: | English |
Summary: | The advent of wireless technologies nowadays gives high impact toward many users to communicate to each other. Wireless Sensor Net-work is a network of nodes which connect to each other by using a device. In addition, transmitting and receiving messages and files are common in most users. There are many platform of network which contributes the same aim that is communication purposes. A ZigBee network is known as one of a platform with its own Standard (IEEE 802.15.4). Unfortunately, ZigBee has a low data rate which limits the capacity of storage in transmitting data. Thus, a large multimedia such as image data are hard to transmit via ZigBee network. Therefore, image compression are necessary in transmission process due to the ability in reducing dimension size and removing redundant image data. In this paper, three method are observed which are stand-alone DWT, stand-alone Huffman, and Hybrid of DWT and Huffman Coding. After conducting a comprehensive observation, it is found that DWT technique are able to compress the image data with less time taken while Huffman technique are suitable in maintaining the quality of image but need a long time to process. Hence, hybrid of DWT with Huffman method are proposed to support each other in terms of compression, computing time and quality of image. |
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