Filtragem de ruído speckle em imagens de radar de abertura sintética por filtros de média não local com transformação homomórfica e distâncias estocásticas

Abstract

The development of new methods and noisy images filtering techniques still attract researchers, which seek to reduce the noise with the minimal loss of details, edges, resolution and removal of fine structures of the image. Moreover, it is extremely important to expand the capacity of the filters for the different noise models present in the Image and Signal Processing literature, like the multiplicative noise speckle, present in the synthetic aperture radar (SAR) images. This Master s degree thesis aims to use a recent denoising algorithm: the nonlocal means (NLM), developed for the additive white gaussian noise (AWGN), and expand, analyze and compare its capacity for intensity SAR images denoising (despeckling), which are contaminated with the speckle. This expansion of the NLM filter is based with the use of the stochastic distances and the comparison of the estimated parameters with de G0 and the inverse Gamma distributions. Finally, this work compares the synthetic and real results of the proposed filter with some filters of the literature.