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• W2000449909 abstract "In this article, a new denoising algorithm is proposed based on the directionlet transform and the maximum a posteriori (MAP) estimation. The detailed directionlet coefficients of the logarithmically transformed noise-free image are considered to be Gaussian mixture probability density functions (PDFs) with zero means, and the speckle noise in the directionlet domain is modelled as additive noise with a Gaussian distribution. Then, we develop a Bayesian MAP estimator using these assumed prior distributions. Because the estimator that is the solution of the MAP equation is a function of the parameters of the assumed mixture PDF models, the expectation-maximization (EM) algorithm is also utilized to estimate the parameters, including weight factors and variances. Finally, the noise-free SAR image is restored from the estimated coefficients yielded by the MAP estimator. Experimental results show that the directionlet-based MAP method can be successfully applied to images and real synthetic aperture radar images to denoise speckle." @default.
• W2000449909 created "2016-06-24" @default.
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• W2000449909 date "2014-02-01" @default.
• W2000449909 modified "2023-10-16" @default.
• W2000449909 title "Directionlet-based method using the Gaussian mixture prior to SAR image despeckling" @default.
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• W2000449909 doi "https://doi.org/10.1080/01431161.2013.875635" @default.
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