Self-Tuning Underwater Image Restoration

Abstract

A self-tuning image restoration filter based on a simplified version of the Jaffe–McGlamery underwater image formation model is presented. Optimal values of the filter parameters are estimated automatically for each individual image by optimizing a quality criterion based on a global contrast measure. The simplified model is ideally suitable for diffuse-light imaging with limited backscatter, but qualitative tests show good performance in a variety of imaging conditions. In addition, quantitative tests with a large number of frames from six real mission videos indicate a substantial performance improvement when restoration is used as a preprocessor for a classifier detecting man-made objects in unconstrained subsea videos.