1.

Gauss-Markov random field model for non-quadratic regularization of complex SAR images

This paper presents despeckling and information extraction using non-quadratic regularization. The novelty of this paper is that instead of the Gaussian prior model a Gauss-Markov random field model is chosen, because it can efficiently model textures in the images. The iterative procedure consist of noise-free image and texture parameter. The experimental results show that the proposed method satisfactorily removes noise form synthetic and real SAR images and is comparable with the state of the art methods using objective measurements on synthetic SAR images.

B.03 Paper at an international scientific conference

COBISS.SI-ID: 12876566

2.

The use of digital signal processing knowledge for image registration

The registration method is based on correlation methods implemented with Fast Fourier Transform (FFT). The Fourier approach was used to match images that are translated, rotated and scaled. The extension of the phase correlation technique is presented here.

B.03 Paper at an international scientific conference

COBISS.SI-ID: 12113686

3.

Despeckling od SAR images

In this paper methods for despeckling os SAR images using Gibbs-Random fields are presented, analysed and evaluated using real SAR images

B.03 Paper at an international scientific conference

COBISS.SI-ID: 13094422