Sidescan Sonar Image Super Resolution Based on Sparse Representation

Abstract

With the rapid development of autonomous underwater vehicles, image produced from sidescan sonar mounted on these vehicles has attracted more and more attention. Many general super resolution approaches can not get satisfied results after applying to sidescan sonar image for its low levels of contrast. Compressive sensing theory suggested that high resolution image can be recovered from low resolution image with sparse representation. After training two dictionaries for high resolution and low resolution image patches, the sparse representation of given low resolution image can be applied to the dictionary of high resolution patch to get super resolution result image. Sparse representation based image super resolution approach applied to sidescan sonar image is discussed.