Journal ArticleDOI
Image reconstruction from multiple frames of sparse data
R. Ramaseshan,B. Yegnanarayana +1 more
TLDR
This method, based on projection onto convex sets (POCS), not only restricts the solution set by satisfying the constraints in the multiple measurements but also reconstructs a high-resolution image.Abstract:
High-resolution image reconstruction from sparse data is an important problem in sensor array imaging (SAI). The reconstructed images from such a data are poorly resolved. However, there may exist possibilities of making multiple measurements, for example, collecting many frames of data in a dynamic scene situation where there is relative motion between the object and the receiver. We discuss here a method of reconstructing good-quality images from multiple frames of sparse data obtained from a simulated dynamic scene situation. This method, based on projection onto convex sets (POCS), not only restricts the solution set by satisfying the constraints in the multiple measurements but also reconstructs a high-resolution image.read more
Citations
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Book ChapterDOI
The Convex Feasibility Problem in Image Recovery
TL;DR: The recovery criterion defines the class of images that are acceptable as solutions to the problem and the recovery method is a numerical algorithm that will produce a solution to the recovery problem, that is, an image that satisfies the recovery criterion as discussed by the authors.
References
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Proceedings ArticleDOI
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Tomaso Poggio,Federico Girosi +1 more
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Michal Irani,Shmuel Peleg +1 more
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Journal ArticleDOI
Nonlinear neural networks: Principles, mechanisms, and architectures
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