Adaptive spatial and multiresolution approach for image denoising

Una Comparación De Reducción De Ruido en Imágenes Digitales Utilizando Un Modelado Estadístico De Coeficientes Wavelet Y Filtrado De Wiener

“…Thus, we can deduce that the high performance of the zerotree-based image coders leads to the development of similar methods for image denoising. In (Chang et al, 2000;Arivazhagan et al, 2011) an image adaptive model was used to perform image denoising via wavelet thresholding using context modeling of the global coefficient histogram. A different approach has been proposed in (Mihcak et al, 1999a) which exploits the local structure of wavelet image coefficients.…”

“…It should be noted that (4) uses the entire wavelet domain resulting in lost in local information leading to poor value of the variance of the wavelet coefficient for f and subsequently poor estimates of its wavelet coefficients. Hence, to overcome the limitations introduced by (4), the proposed approach uses equation 5where the maximum likelihood criterium estimates ., 1999a;Arivazhagan et al, 2011), inspired by a compression method previously published in (Lo Presto et al, 1997). These models assume the existence of an unknown smooth space-variant variance field.…”