DocumentCode :
612933
Title :
An efficient VLSI architecture for 2-D dual-mode SMDWT
Author :
Chih-Hsien Hsia ; Jen-Shiun Chiang ; Shih-Hao Chang
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
fYear :
2013
fDate :
10-12 April 2013
Firstpage :
775
Lastpage :
779
Abstract :
In this paper, we propose a highly efficient VLSI architecture for 2-D dual-mode (supporting 5/3 and 9/7 lifting-based) Symmetric Mask-based Discrete Wavelet Transform (SMDWT) to improve the critical issue of the 2-D Lifting-based Discrete Wavelet Transform (LDWT), and then obtains the benefit of low-latency reduced complexity, and low transpose memory. The SMDWT also has the advantages of reduced complexity, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. The transpose memory requirement of the N×N is 9N. The architecture is based on the parallel and folding scheme processing to achieve higher hardware utilization ratio and reduce the silicon area. It is suitable for Very Large Scale Integration (VLSI) implementation and can be applied to real-time operating of computer vision applications.
Keywords :
VLSI; computer vision; discrete wavelet transforms; transform coding; 2D dual-mode SMDWT; 2D dual-mode symmetric mask-based discrete wavelet transform; 2D lifting-based discrete wavelet transform; LDWT; VLSI architecture; computer vision application; folding scheme processing; high hardware utilization ratio; independent subband coding processing; latency time reduction; low transpose memory; low-latency complexity reduction; parallel scheme processing; regular signal coding; short critical path; very large scale integration implementation; Biomedical imaging; CMOS integrated circuits; CMOS technology; Discrete wavelet transforms; Image recognition; Irrigation; Very large scale integration; Symmetric mask-based discrete wavelet transform; VLSI; dicrete wavelet transform; parallel and folding scheme;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on
Conference_Location :
Evry
Print_ISBN :
978-1-4673-5198-0
Electronic_ISBN :
978-1-4673-5199-7
Type :
conf
DOI :
10.1109/ICNSC.2013.6548836
Filename :
6548836
Link To Document :
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