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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jing Li Zhichao Lu Gang Zeng Rui Gan Hongbin Zha |
| Copyright Year | 2014 |
| Description | Author affiliation: Key Lab. on Machine Perception, Peking Univ., Beijing, China (Jing Li; Zhichao Lu; Gang Zeng; Rui Gan; Hongbin Zha) |
| Abstract | This paper describes a patchwork assembly algorithm for depth image super-resolution. An input low resolution depth image is disassembled into parts by matching similar regions on a set of high resolution training images, and a super-resolution image is then assembled using these corresponding matched counterparts. We convert the super resolution problem into a Markov Random Field (MRF) labeling problem, and propose a unified formulation embedding (1) the consistency between the resolution enhanced image and the original input, (2) the similarity of disassembled parts with the corresponding regions on training images, (3) the depth smoothness in local neighborhoods, (4) the additional geometric constraints from self-similar structures in the scene, and (5) the boundary coincidence between the resolution enhanced depth image and an optional aligned high resolution intensity image. Experimental results on both synthetic and real-world data demonstrate that the proposed algorithm is capable of recovering high quality depth images with X4 resolution enhancement along each coordinate direction, and that it outperforms state-of-the-arts [14] in both qualitative and quantitative evaluations. |
| Starting Page | 3374 |
| Ending Page | 3381 |
| File Size | 1085965 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781479951185 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2014.431 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-23 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image resolution Training Databases Assembly DH-HEMTs Energy resolution Image edge detection Self-similarity Dpeth map super resolution Disassemble |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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