Abstract: Now most super-resolution reconstruction algorithms are applied to atmospheric picture restoration. Taking the complexity of underwater optical environment into consideration, it is hard to perform direct processes towards scattering and attenuation caused by water simply by transplanting those super-resolution reconstruction algorithms to underwater images. In such condition, an underwater image super-resolution reconstruction algorithm based on optical imaging model is proposed by integrating different imaging models. Firstly, aiming at the severe degradation in image quality caused by light scattering in water, dark channel prior is used, based on underwater optical imaging model, to estimate scattered light and transmission in observed data to produce the result of noise estimation. Secondly, super-resolution reconstruction of projection onto convex sets is performed on the low-resolution image sequence from which scattered light is removed in order to produce a high-resolution image. At last, aiming at overcoming the decrease in intensity and blur caused by water so as to produce the restored image, light compensation is conducted on the high-resolution image using transmission. By comparing the reconstructed images produced by the proposed algorithm with those produced by classical super-resolution algorithms, quality improvement in restored images by our algorithm is proved in algorithm simulation.
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Key words: underwater image, super-resolution reconstruction, optical imaging model, dark channel prior