DocumentCode
1351786
Title
Reconstruction from 2-D wavelet transform modulus maxima using projection
Author
Liew, A. W C ; Law, N.F.
Author_Institution
Dept. of Electron. Eng., Hong Kong Univ., Hong Kong
Volume
147
Issue
2
fYear
2000
fDate
4/1/2000 12:00:00 AM
Firstpage
176
Lastpage
184
Abstract
Wavelet transform modulus maxima can be used to characterise sharp variations such as edges and contours in an image. The authors analyse the a priori constraints present in the wavelet transform modulus maxima representation. A new projection-based algorithm which enforces all the a prior constraints in the representation is proposed. Quadratic programming is used to obtain a sequence which satisfies the maxima constraint. Thus realising the projection onto the maxima constraint space. To save computation, an approximate method to obtain a sequence which satisfies the maxima constraint is given. The new algorithm is shown to provide better solution than the original reconstruction algorithm of Mallat and Zhong (1992). The authors also propose a simple method to accelerate the algorithm. The acceleration is achieved by the incorporation of a momentum term which exploits the high correlation between the difference images between two consecutive iterations. The simulation results show that the proposed algorithm gives good reconstruction and the simple acceleration method can significantly improve the convergence rate
Keywords
convergence of numerical methods; image reconstruction; image representation; iterative methods; quadratic programming; wavelet transforms; 2D wavelet transform modulus maxima; a prior constraints; acceleration method; consecutive iterations; convergence rate; difference images; image reconstruction; image representation; maxima constraint space; momentum term; projection-based algorithm; quadratic programming; sharp variations characterisation; simulation results;
fLanguage
English
Journal_Title
Vision, Image and Signal Processing, IEE Proceedings -
Publisher
iet
ISSN
1350-245X
Type
jour
DOI
10.1049/ip-vis:20000206
Filename
848580
Link To Document