Simultaneous estimation of super-resolved intensity and depth maps from low resolution defocused observations of a scene

Proceedings of the IEEE International Conference on Computer Vision

Volumn 1, Issue , 2001, Pages 113-118

  Rajan, Deepu ^a   Chaudhuri, Subhasis ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; FEATURE EXTRACTION; IMAGE QUALITY; IMAGE SENSORS; IMAGING SYSTEMS; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION; SIMULATED ANNEALING; VIDEO CAMERAS;

HIGH RESOLUTION IMAGE ACQUISITION; MARKOV RANDOM FIELD; MAXIMUM A POSTERIORI ESTIMATION; SUPER-RESOLVED INTENSITY;

IMAGE RETRIEVAL;

EID: 0034850091     PISSN: None     EISSN: None     Source Type: Journal    
DOI: 10.1109/ICCV.2001.937506     Document Type: Article

References (17)

1. Depth of scene from depth of field
2. A new sense for depth of field
3. Parallel depth recovery by changing camera parameters
4. Minimal operator set for passive DFD
5. Depth from defocus vs stereo: How different really are they?
6. An MRF model based approach to simultaneous recovery of depth and restoration from defocused images
7. Multiframe image restoration and registration
8. Improving resolution by image registration
9. High resolution image reconstruction from lower-resolution image sequences and space-varying image restoration
10. A Bayesian approach to image expansion for improved definition
11. Motion deblurring and super-resolution from an image sequence
12. Restoration of a single super-resolution image from several blurred, noisy and undersampled measured images
13. Efficient super-resolution via image warping
14. Sub-pixel bayesian estimation of albedo and height
15. Super-resolved surface reconstruction from multiple images
16. Stochastic relaxation, Gibbs distribution and the Bayesian restoration of image