UTHM Institutional Repository

Medical Image Compression using Standard Deviation-Based Wavelet Coefficients Thresholding Method

Md Taujuddin, Nik Shahidah Afifi and Ibrahim, Rosziati and Sari, Suhaila (2019) Medical Image Compression using Standard Deviation-Based Wavelet Coefficients Thresholding Method. In: FACULTY OF APPLIED SCIENCE AND TECHNOLOGY TECHNICAL REPORT 2018. PENERBIT UTHM, UTHM, pp. 117-127. ISBN 978-967-2306-23-8

[img]
Preview
PDF
shahidah.pdf

Download (413kB)

Abstract

In recent decades, digital images have become increasingly important. With many modern applications use image graphics extensively, it tends to burden both the storage and transmission process. Despite the technological advances in storage and transmission, the demands placed on storage and bandwidth capacities still exceeded its availability. Moreover, the compression process involves eliminating some data that degrades the image quality. Therefore, to overcome this problem, an improved thresholding and quantization techniques for image com-pression is proposed. Firstly, the generated wavelet coefficients obtained from the Discrete Wavelet Transform (DWT) process are thresholded by the proposed Standard Deviation-Based Wavelet Coefficients Threshold Estimation Algorithm. The proposed algorithm estimates the best threshold value at each detail subbands. This algorithm exploits the huge number of near-zero coefficients exist in detail subbands. For different images, the distribution of wavelet coefficients at each subband are substantially different. So, by calculating the standard deviation value of each subband, a better threshold value can be obtained. The results are then compared to the existing algorithms and it is found that the proposed compression algorithm shows double increase in compression ratio performance, produces higher image quality with PSNR value above 40dB.

Item Type: Book Section
Subjects: T Technology > T58.5-58.64 Information technology
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
Depositing User: Mrs. Nik Shahidah Afifi Md Taujuddin
Date Deposited: 31 Oct 2019 02:39
Last Modified: 31 Oct 2019 02:39
URI: http://eprints.uthm.edu.my/id/eprint/11823
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year