JOURNAL ARTICLE

Super-resolution image reconstruction for Omni-Vision based on POCS

Abstract

The catadioptric omnidirectional sensor, called Omni-Vision, involving capture and automatic interpretation of images, depicts full horizontal panorama 360 degrees view of the surroundings. The field of view band can be easily transformed to a panoramic image and a conventional perspective image. However, it has an intrinsical disadvantage that the angular resolution Omni-Vision is lower than that of conventional video camera. In this paper, a super-resolution method for the Omni-Vision is proposed to reconstruct high resolution panoramic transformed images, in which consecutive images obtained by rotating motion of Omni-Vision are fused using the POCS (project on convex sets) algorithm. Experiment results are also provided to demonstrate the efficiency of the proposed method.

Keywords:
Catadioptric system Computer vision Artificial intelligence Panorama Computer science Perspective (graphical) Field of view Iterative reconstruction Image resolution Machine vision Lens (geology) Optics Physics

Metrics

9
Cited By
1.24
FWCI (Field Weighted Citation Impact)
11
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology

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