An Object Enhancement Method For Forward-Looking Sonar Images Based On Multi-Frame Fusion

Forward-looking sonar (FLS) often suffers from complex underwater environments. It is hard to detect small objects from the FLS imagery characterized by low signal-to-noise ratio and low resolution. To highlight the object from severe noise background, we propose an object enhancement method for objects in the regions of interest (ROIs) based on multi-frame image fusion. This method includes two crucial steps: 1) A Fourier-based multi-stage registration algorithm is proposed to solve the problem of a drastic change of object position between frames due to long target distance and rapid change of azimuth angle. 2) A multi-frame fusion algorithm based on self-supervised deep learning is adopted to enhance the ROIs. Experimental results demonstrate that our proposed enhancement method can significantly highlight the objects in the ROIs and has excellent noise suppression in terms of quantitative metrics and visual quality.