8 December 2011 Nonlocal means SAR image despeckling using Principle Neighborhood Dictionaries
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Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 80021N (2011); doi: 10.1117/12.902415
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
The Principle Neighborhood Dictionary (PND) filter projects the image patches onto a lower dimensional subspace using Principle Component analysis (PCA), based on which the similarity measure of image patch can be computed with a higher accuracy for the nonlocal means (NLM) algorithm. In this paper, a new PND filter for synthetic aperture radar (SAR) image despeckling is presented, in which a new distance that adapts to the multiplicative speckle noise is derived. Compared with the commonly used Euclidean distance in NLM, the new distance measure improves the accuracy of the similarity measure of speckled patches in SAR images. The proposed method is validated on simulated and real SAR images through comparisons with other classical despeckling methods.
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Hua Zhong, Chen Yang, L. C. Jiao, "Nonlocal means SAR image despeckling using Principle Neighborhood Dictionaries", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80021N (8 December 2011); doi: 10.1117/12.902415; https://doi.org/10.1117/12.902415
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KEYWORDS
Synthetic aperture radar

Image filtering

Speckle

Image enhancement

Device simulation

Distance measurement

Associative arrays

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