Optically coherent image formation and denoising using a plug and play inversion framework
| Autor: | Charles A. Bouman, Skip Williams, Russell Trahan, Michael Shao, Stacie Williams, Casey J. Pellizzari, Hanying Zhou, Bijan Nemati |
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| Rok vydání: | 2017 |
| Předmět: |
Synthetic aperture radar
Image formation Computer science Materials Science (miscellaneous) Noise reduction Gaussian ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Iterative reconstruction 01 natural sciences Industrial and Manufacturing Engineering 010309 optics symbols.namesake Optics 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Maximum a posteriori estimation Heterodyne detection Business and International Management business.industry Speckle noise Inverse problem symbols 020201 artificial intelligence & image processing business Algorithm |
| Zdroj: | Applied optics. 56(16) |
| ISSN: | 1539-4522 |
| Popis: | The performance of optically coherent imaging systems can be limited by measurement and speckle noise. In this paper, we develop an image formation framework for computing the maximum a posteriori estimate of an object's reflectivity when imaged using coherent illumination and detection. The proposed approach allows for the use of Gaussian denoising algorithms (GDAs), without modification, to mitigate the exponentially distributed and signal-dependent noise that occurs in coherent imaging. Several GDAs are compared using both simulated and experimental data. The proposed framework is shown to be robust to noise and significantly reduce reconstruction error compared to the standard inversion technique. |
| Databáze: | OpenAIRE |
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