Ship detection in satellite imagery using rank-order grayscale hit-or-miss transforms

Neal R. Harvey; Reid Porter; James Theiler

doi:10.1117/12.850886

15 April 2010 Ship detection in satellite imagery using rank-order grayscale hit-or-miss transforms

Neal R. Harvey, Reid Porter, James Theiler

Proceedings Volume 7701, Visual Information Processing XIX; 770102 (2010) https://doi.org/10.1117/12.850886
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of the transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.

Citation Download Citation

Neal R. Harvey, Reid Porter, and James Theiler "Ship detection in satellite imagery using rank-order grayscale hit-or-miss transforms", Proc. SPIE 7701, Visual Information Processing XIX, 770102 (15 April 2010); https://doi.org/10.1117/12.850886

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