Title :
Image distance based ship detection using SAR images
Author :
Bo, Hua ; Ma, Fulong
Author_Institution :
Inf. Eng. Dept., Shanghai Maritime Univ., Shanghai
Abstract :
A novel method is developed for ship detection in synthetic aperture radar (SRA) images, which is based on image distance computation techniques. Using a second-order hidden Markov mesh model to learn statistical models of images, one can obtain the distance of two images for the purpose of detecting ships. First, the features of an image can be extracted using a method that best matches its statistical model, which is related to dynamic programming. Second, given the state transition matrix and observation distributions within states, statistical distance between images based on the similarity of their statistical models can be estimated. Experimental results demonstrate that this ship detection algorithm can effectively enhance ship target as well as suppress speckle and has better detection precision and lower calculation complexity.
Keywords :
feature extraction; hidden Markov models; mesh generation; radar target recognition; ships; speckle; statistical analysis; synthetic aperture radar; SAR images; detection precision; dynamic programming; feature extraction; image distance computation; second-order hidden Markov mesh model; ship detection; speckle suppression; state transition matrix; statistical models; synthetic aperture radar; Change detection algorithms; Condition monitoring; Detection algorithms; Hidden Markov models; Marine vehicles; Object detection; Radar detection; Random variables; Speckle; Synthetic aperture radar;
Conference_Titel :
Networking, Sensing and Control, 2009. ICNSC '09. International Conference on
Conference_Location :
Okayama
Print_ISBN :
978-1-4244-3491-6
Electronic_ISBN :
978-1-4244-3492-3
DOI :
10.1109/ICNSC.2009.4919358