Regularization blind restoration of underwater images based on particle swarm optimization
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Received Date:
2014-08-18
Accepted Date:
2014-09-22
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Abstract
Difficulties of underwater image restoration lies in lack of enough information about the point spread function of sea water which induces the ill-posed problem consequently. In order to improve the imaging quality of underwater laser imaging system, a blind image restoration algorithm based on particle swarm optimization regularization parameter was proposed. This method integrated the technique characteristics of Tikhonov regularization and the improved total variation(TV) regularization. An alternating iterative method was adopted to estimate point spread function and restored image respectively. Meanwhile, the regularization parameter was optimized by using particle swarm algorithm. After dealing with the simulation images and the actual underwater images, the results of underwater image restoration show that this method has good robustness for underwater image restoration and the algorithm is convergent and stable.
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