Name
Abstract | ||
|---|---|---|
This paper presents a hierarchical stereo correspondence matching technique based on multiwavelet transforms. A global error energy minimization technique is employed to generate a disparity map for each of the four multiwavelet approximation subband pairs. The information in the four disparity maps is then combined using a Fuzzy algorithm to generate a single disparity map. This initial disparity map is estimated at the lowest resolution and needs to be progressively passed on to higher resolution levels. Hence, the search at higher resolution levels is significantly reduced, thereby reducing the computational cost of the overall process and improving the reliability of the final disparity map. Results show that the proposed technique produces a smoother disparity map with less mismatch errors compared to applying the same method in both spatial and wavelet domains. The proposed algorithm fares very well when compared to other state of art techniques from the Middlebury database. |
Year | Venue | Keywords |
|---|---|---|
2011 | Barcelona | approximation theory,fuzzy set theory,image matching,image resolution,stereo image processing,wavelet transforms,middlebury database,computational cost,disparity maps,fuzzy algorithm,global error energy minimization technique,hierarchical multiwavelet based stereo correspondence matching technique,higher resolution levels,multiwavelet approximation subband pairs,multiwavelet transforms,spatial domains,wavelet domains,stereo vision,minimization |
Field | DocType | ISSN |
Pattern recognition,Stereopsis,Fuzzy logic,Minification,Artificial intelligence,Global error,Image resolution,Mathematics,Energy minimization,Wavelet,Wavelet transform | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pooneh Bagheri Zadeh | 1 | 6 | 3.86 |
| Cristian Vasile Serdean | 2 | 3 | 1.22 |