MATLAB PROJECT
Radar Image Series
Denoising of Space Targets Based on Gaussian Process Regression
Abstract:
We address the problem of image series
denoising for high-resolution radar in a nonparametric Bayesian framework. By
exploiting the characteristics of amplitude variation at different pixels in
the image series, we impose the Gaussian process (GP) model to the
corresponding time series of each pixel and achieve effective image series
denoising by GP regression. Particularly, the model parameters are solved
conveniently by the maximum likelihood estimation. Compared with available
denoising techniques in the data domain, spatial domain, and image frequency
domain, the proposed method has exhibited more flexibility in data description
and better performance in structure preserving and denoising, especially in low
signal-to-noise ratio scenarios.
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