Fast Denoising of Sonar Image Based on Saliency Detection

Sonar image is inevitably contaminated by noise during the acquisition process, while the noise reduction algorithms with good performance are usually of high time complexity. The human visual attention mechanism usually guides the eyes to salient region and gives priority to those visual information. In view of this, saliency detection based on manifold ranking was introduced into sonar image processing, to divide the image into two parts: salient region and non-significant region. For the salient region with small proportion, block-matching and 3-D filtering (BM3D) algorithm was adopted to reduce noise and protect the main information of the image; for the non-significant background which was not very concerned, high efficiency mean filtering was used. On the collected sonar image data set, the present algorithm was compared with the classic MF and BM3D algorithms through the subjective and 2 objective evaluation indexes. The experimental results show that the efficiency of the present algorithm is much higher than that of BM3D, while the image visual effect is guaranteed, which is satisfied with the real-time application requirement of autonomous underwater vehicles. © 2019 Journal of Northwestern Polytechnical University.