A fast adaptive guided filtering algorithm for light field depth interpolation
Light field camera provides 4D information of the light rays, from which the scene depth information can be inferred. The disparity/depth maps calculated from light field data are always noisy with missing and false entries in homogeneous regions or areas where view-dependant effects are present. In...
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| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/100768 http://hdl.handle.net/10220/25707 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Light field camera provides 4D information of the light rays, from which the scene depth information can be inferred. The disparity/depth maps calculated from light field data are always noisy with missing and false entries in homogeneous regions or areas where view-dependant effects are present. In this paper we proposed an adaptive guided filtering (AGF) algorithm to get an optimized output disparity/depth map. A guidance image is used to provide the image contour and texture information, the filter is able to preserve the disparity edges, smooth the regions without influence of the image texture, and reject the data entries with low confidence during coefficients regression. Experiment shows AGF is much faster in implementation as compared to other variational or hierarchical based optimization algorithms, and produces competitive visual results. |
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