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Point Spread Function Model-based Projections onto Convex Sets Reconstruction for Laser Imaging in Water
Y-Z. Chen, M. Xia, W. Li, D-Q. Chen and K-C Yang

The visibility of underwater imaging illuminated by a laser beam has been of long-standing interest. Image denoising and restoration can help to enhance the image quality; however, the resolution is still limited. Image super resolution reconstruction (SRR) is a widely used technique for improving resolution beyond the limit of hardware. Projections onto convex sets (POCS) is one of the most popular SRR methods for its flexibility of incorporating prior knowledge such as the point spread function (PSF) of imaging system. A better understanding of the PSF can improve the accuracy of the POCS method, thus, the presented effort reviews several PSF models including a simplified PSF model based on beam propagation and applies them to the POCS method for an underwater range-gated pulsed laser imaging system. From experimental results, we can conclude that the combination of PSF can effectively enhance the performance of the POCS reconstruction for underwater laser imaging.

Keywords: Image evaluation, modulation transfer function, super resolution reconstruction (SRR), projections onto convex sets (POCS), point spread function (PSF), range-gated, gray mean grads, Laplacian sum, information capacity

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