| Paper: | IMDSP-P10.11 | ||
| Session: | Image Analysis | ||
| Time: | Thursday, May 20, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Analysis | ||
| Title: | A NEW NON-LINEAR EXPONENTIAL 2-D ADAPTIVE FILTER AND ITS APPLICATION IN TEXTURE CHARACTERIZATION | ||
| Authors: | Mounir Sayadi; ESSTT | ||
| Samir Sakrani; ESSTT | |||
| Farhat Fnaiech; ETS | |||
| Mohamed Cheriet; ETS | |||
| Abstract: | We propose in this paper a new non-linear exponential adaptive bi-dimensional (2-D) filter for image modeling. The filter coefficients are updated with the Least Mean Square (LMS) algorithm. Furthermore, the proposed non-linear model is used for texture modeling with a 2-D Auto-Regressive (AR) adaptive model. The characterization efficiency of the proposed exponential model is compared with the 2-D linear AR model updated with the LMS algorithm. The comparison criteria is based on the computation of a characterization rate using the ratio of ''between-class'' variances with respect to ''within-class'' variances of the estimated coefficients. Extensive experiments show that the exponential model coefficients give better results in texture discrimination than those of the linear model, even in a noisy context. | ||
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