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In this paper, a novel despeckling method based on Gaussian scale mixtures (GSM) model in the directionlet domain is proposed. Before despeckling, we define a measurement of directivity of texture to calculate the directivity of texture according to the edge map. After directionlet transform, neighborhoods of coefficients at adjacent scales are modeled as GSM model. Under this model, a Bayes Least...
In this paper a new method of speckle reduction of SAR images in curvelet domain is proposed. In the method, curvelet transform is integrated with wavelet filtering. The new method consists of five parts: preprocessing, curvelet transform (CT), curvelet coefficients processing and two inverse transforms. In the preprocessing step, homomorphic transform is applied to convert multiplicative noise in...
This paper proposes a novel method on synthetic aperture radar (SAR) Image denoising, which is based on context modeling combined with multiscale orthogonal bandlet coefficients. For the main influence of SAR image is multiplicative speckle noise, the logarithm uniform transform is used to convert it to additive noise. In this paper, the multiscale orthogonal bandlet transform is applied to noisy...
Addressing SAR image speckle denoising, this dissertation proposes a new method based on dual tree complex wavelet transformation combined with modification to them according to significant coefficient rule. In the method, a thresholding method are adapted for each selected subband based on the nonlinear functions. The nonlinear functions are based on sigmoid functions. And then, the wavelet coefficients...
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