Abstract
This paper presents a super-resolution image reconstruction from a sequence of aliased imagery. The sub-pixel shifts (displacement) among the images are unknown due to uncontrolled natural jitter of the imager. A correlation method is utilized to estimate sub-pixel shifts between each low-resolution aliased image with respect to a reference image. An error-energy reduction algorithm is derived to reconstruct the high-resolution alias-free output image. The main feature of this proposed error-energy reduction algorithm is that we treat the spatial samples from low-resolution images that possess unknown and irregular (uncontrolled) sub-pixel shifts as a set of constraints to populate an over-sampled (sampled above the desired output bandwidth) processing array. The estimated sub-pixel locations of these samples and their values constitute a spatial domain constraint. Furthermore, the bandwidth of the alias-free image (or the sensor imposed bandwidth) is the criterion used as a spatial frequency domain constraint on the over-sampled processing array. The results of testing the proposed algorithm on the simulated low-resolution aliased images from real world non-aliased FLIR (Forward-Looking Infrared) images, real world aliased FLIR images and visible aliased images are provided.
Original language | English (US) |
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Article number | 18 |
Pages (from-to) | 114-124 |
Number of pages | 11 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 5784 |
DOIs | |
State | Published - 2005 |
Externally published | Yes |
Event | Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI - Orlando, FL, United States Duration: Mar 30 2005 → Apr 1 2005 |
Keywords
- Aliased imagery
- Error-energy reduction
- Sub-pixel shift estimation
- Super-resolution image reconstruction
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering