Wavelet Transform has been successfully applied in different fields, ranging from pure mathematics to applied sciences. Numerous studies carried out on Wavelet Transform have proven its advantages in image processing and data compression. Recent progress has made it the basic encoding technique in data compression standards. Pure software implementations of the Discrete Wavelet Transform, however, appear to be the performance bottleneck in real-time systems. Therefore, hardware acceleration of the Discrete Wavelet Transform has become a topic of interest. The goal of this paper is to investigate the feasibility of hardware acceleration of Discrete Wavelet Transform for image compression applications, and to compare the performance improvement against the software implementation. In this paper, a design for efficient hardware acceleration of the Discrete Wavelet Transform is proposed. The hardware is designed to be integrated as an extension to custom-computing platform and can be used to accelerate multimedia applications as JPEG2000.
[1]
Stéphane Mallat,et al.
Multifrequency channel decompositions of images and wavelet models
,
1989,
IEEE Trans. Acoust. Speech Signal Process..
[2]
C. Mulcahy,et al.
Image compression using the Haar wavelet transform
,
2000
.
[3]
Antonio Ortega,et al.
Modeling of contours in wavelet domain for generalized lifting image compression
,
2009,
2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[4]
Hongsong Li,et al.
A new image coding scheme based upon image pattern recognition
,
2010,
2010 IEEE International Conference on Intelligent Computing and Intelligent Systems.
[5]
D. Shah,et al.
Efficient Implementations of Discrete Wavelet Transforms Using Fpgas
,
2011
.
[6]
Harmanpreet Kaur,et al.
Comparative analysis of wavelet transform and wavelet packet transform for image compression at decomposition level 5
,
2013,
ARTCom 2013.