@inproceedings{c1ccf76cdbc941299574f2a7020dfb2a,
title = "The application of lifting DWT in digital image processing",
abstract = "Discrete wavelet transform (DWT) has shown great performance in digital image compression and denoising applications. It has been the transformation used for source encoding in JPEG2000 still image compression standard and FBI wavelet scalar quantization. This paper has adopted the lifting DWT which is the most computation-efficient scheme of wavelet analysis and outlines the multi-resolution features of the wavelet transform. Details of the lifting wavelet transform are analyzed to propose a high-speed, less-area and power-efficient digital image compression scheme. Maple 15 has been employed for design and simulation studies.",
author = "Azadeh Safari and Yinan Kong",
year = "2013",
doi = "10.1007/978-3-642-31528-2_71",
language = "English",
isbn = "9783642315275",
volume = "178 LNEE",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer, Springer Nature",
number = "VOL. 3",
pages = "449--453",
editor = "David Jin and Sally Lin",
booktitle = "Advances in Mechanical and Electronic Engineering",
address = "United States",
note = "2012 International Conference on Mechanical and Electronic Engineering, ICMEE 2012 ; Conference date: 23-06-2012 Through 24-06-2012",
}