Sidescan Sonar Image Processing: Correcting Brightness Variation and Patching Gaps

Sidescan sonar data are typically presented as gray level images. However, sidescan images often show striking variations in brightness. These variations, caused by the sonar beam pattern and the constantly changing attitude of the tow-fish, make the images difficult to read as pictures of the seabed. This reduces the utility of the images for marine geologists. In this paper, the effects of the sonar beam pattern across the swath are corrected using a normalization process based on the average signal intensity for cacti grazing angle. Noise along the track, which is generally caused by changes in the attitude of the towfish. is eliminated using an assumption that the total hack-scattered energy from each ping should he similar to adjacent pings in the time series. These two processes allow the production of smooth and clear waterfall displays. However, when the sidescan data are projected onto a map as a high resolution ”mosaic” image, gaps appear on the outer edge of the swath where the towfish changes course. To remove the gaps, a patching algorithm is proposed. The patching method is justified theoretically by the shape of the sonar footprint on the sea floor. All the pixels falling inside the sonar footprint can he assigned reasonable values using just the original data series, with no need for interpolation.

並列關鍵字

sidescan ； sonar ； brightness ； gap patching ； mosaic ； footprint

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