Dense disparity estimation using Gabor filters and image derivatives

We tackle the recurrent problem of disparity estimation since the mapping from disparity to depth is well understood while the automatic disparity extraction is still subject to errors. We propose to use the image derivatives with the phase-based approach to overcome the tuning problem of the filter...

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Bibliographic Details
Published inProceedings, Second International Conference on 3-D Digital Imaging and Modeling : October 4-8, 1999, Ottawa, Canada pp. 483 - 489
Main Authors Ouali, M., Ziou, D., Laurgeau, C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
Band pass filters
Cepstral analysis
Dynamic programming
Electrical capacitance tomography
Error analysis
Frequency
Gabor filters
Image reconstruction
Robotics and automation
Satellites
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ISBN9780769500621
0769500625
DOI10.1109/IM.1999.805380

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Summary:We tackle the recurrent problem of disparity estimation since the mapping from disparity to depth is well understood while the automatic disparity extraction is still subject to errors. We propose to use the image derivatives with the phase-based approach to overcome the tuning problem of the filter. Moreover we propose a quadratic model for the singularities neighborhood detection. The approach is characterized by the simplicity of its implementation. It also provides dense and accurate disparity maps. A numerical error analysis shows that the results are very satisfactory.
ISBN:9780769500621
0769500625
DOI:10.1109/IM.1999.805380