Paper Info
Title
Stereo correspondence matching: Balanced multiwavelets versus unbalanced multiwavelets
Abstract
This paper investigates the efficiency of unbalanced versus balanced multiwavelets in stereo correspondence matching. A multiwavelet transform is first applied to a pair of stereo images to decorrelate them into a number of subbands. Information in the approximation subbands of an unbalanced multiwavelet carries different spectral content of the input image while the balanced multiwavelet approximation subbands produce similar spectral content of the input image. Hence, the application of the approximation subbands of the unbalanced multiwavelets in disparity map generation could produce more accurate results compared to that of balanced multiwavelets. A global error energy minimization technique is employed to generate a disparity map for each approximation subband. The information in the resulting disparity maps is then combined using a Fuzzy algorithm to generate a dense disparity map. Simulation results show that the unbalanced multiwavelets produce a smoother disparity map with less mismatch errors compared to that of balanced multiwavelets.
Year
Venue
Keywords
2010
Aalborg
approximation theory,fuzzy set theory,image matching,minimisation,stereo image processing,wavelet transforms,balanced multiwavelets approximation subband,fuzzy algorithm,global error energy minimization technique,multiwavelet transform,smoother disparity map generation,spectral content,stereo correspondence image matching,unbalanced multiwavelets approximation subband,decision support systems,signal processing
Field
DocType
ISSN
Signal processing,Computer vision,Fuzzy logic,Algorithm,Artificial intelligence,Global error,Mathematics,Energy minimization
Conference
2219-5491
Citations 
PageRank 
References 
1
0.37
10
Authors
2
Name
Order
Citations
PageRank
Pooneh Bagheri Zadeh163.86
Cristian Vasile Serdean231.22