28 June 2018 Histogram-based perceptual hash algorithm for synthetic aperture radar image segmentation
Jian Ji, Linyi Han, Jiajie Wei, Xiaojia Lü, XIaoyuan Li
Author Affiliations +
Abstract
To speed up the segmentation procedure and improve the segmentation quality of synthetic aperture radar (SAR) image, this paper presents an adaptive unsupervised SAR image segmentation method, which is integrated in the grayscale histogram and perceptual hash algorithm. The final clusters can be acquired self-adaptively without predefining. The two stages of the algorithm are discussed in details: histogram-based preprocessing and region merging. In preprocessing, histogram-based gray-level reduction is adopted to generate the set of initial segmented regions to address the problem of over-segmentation. When merging regions, the similarity of different regions can be obtained by comparing their different fingerprints calculated in the perceptual hash algorithm, which is the kernel of the whole SAR image segmentation method. The application of the perceptual hash algorithm for image segmentation can reduce the computational complexity and improve the efficiency of region merging. Experimental simulations and theoretical analysis are used to demonstrate the effectiveness of this algorithm.
© 2018 SPIE and IS&T 1017-9909/2018/$25.00 © 2018 SPIE and IS&T
Jian Ji, Linyi Han, Jiajie Wei, Xiaojia Lü, and XIaoyuan Li "Histogram-based perceptual hash algorithm for synthetic aperture radar image segmentation," Journal of Electronic Imaging 27(3), 033044 (28 June 2018). https://doi.org/10.1117/1.JEI.27.3.033044
Received: 24 January 2018; Accepted: 1 June 2018; Published: 28 June 2018
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Cited by 1 scholarly publication and 1 patent.
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KEYWORDS
Image segmentation

Image processing algorithms and systems

Synthetic aperture radar

Binary data

Image filtering

Speckle

Image compression

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