Bibliographic Details
| Title: |
Learning to Sense for Coded Diffraction Imaging. |
| Authors: |
Hyder, Rakib1 (AUTHOR), Cai, Zikui1 (AUTHOR), Asif, M. Salman1 (AUTHOR) sasif@ucr.edu |
| Source: |
Sensors (14248220). Dec2022, Vol. 22 Issue 24, p9964. 15p. |
| Subject Terms: |
*OVERHEAD costs, *IMAGE reconstruction |
| Abstract: |
In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase retrieval method as an unrolled network with a fixed number of layers where each layer of the network corresponds to a single step of iteration, and we minimize the recovery error by optimizing over the illumination patterns. Since the number of iterations/layers is fixed, the recovery has a fixed computational cost. Extensive experimental results on a variety of datasets demonstrate that our proposed method significantly improves the quality of image reconstruction at a fixed computational cost with illumination patterns learned only using a small number of training images. [ABSTRACT FROM AUTHOR] |
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| Database: |
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