Paper
11 March 2005 Super-resolution image synthesis using projections onto convex sets in the frequency domain
Author Affiliations +
Proceedings Volume 5674, Computational Imaging III; (2005) https://doi.org/10.1117/12.605436
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
Optical imaging systems are often limited in resolution, not by the imaging optics, but by the light intensity sensors on the image formation plane. When the sensor size is larger than the optical spot size, the effect is to smooth the image with a rectangular convolving kernel with one sample at each non-overlapping kernel position, resulting in aliasing. In some such imaging systems, there is the possibility of collecting multiple images of the same scene. The process of reconstructing a de-aliased high-resolution image from multiple images of this kind is referred to as “super-resolution image reconstruction.” We apply the POCS method to this problem in the frequency domain. Generally, frequency domain methods have been used when component images were related by subpixel shifts only, because rotations of a sampled image do not correspond to a simple operation in the frequency domain. This algorithm is structured to accommodate rotations of the source relative to the imaging device, which we believe helps in producing a well-conditioned image synthesis problem. A finely sampled test image is repeatedly resampled to align with each observed image. Once aligned, the test and observed images are readily related in the frequency domain and a projection operation is defined.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frederick W. Wheeler, Ralph T. Hoctor, and Eamon B. Barrett "Super-resolution image synthesis using projections onto convex sets in the frequency domain", Proc. SPIE 5674, Computational Imaging III, (11 March 2005); https://doi.org/10.1117/12.605436
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CITATIONS
Cited by 16 scholarly publications and 85 patents.
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KEYWORDS
Point spread functions

Lawrencium

Image sensors

Sensors

Imaging systems

Spatial frequencies

Super resolution

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