Estimation of D Noisy Fractional Brownian Motion and its Applications using Wavelets
نویسندگان
چکیده
The D fractional Brownian motion fBm model is useful in describing natural scenes and textures Most fractal estimation algorithms for D isotropic fBm images are simple extensions of the D fBm estimation method This method does not perform well when the image size is small say We propose a new algorithm that estimates the fractal parameter from the decay of the variance of the wavelet coe cients across scales Our method places no restriction on the wavelets Also it provides a robust parameter estimation for small noisy fractal images For image denoising a Wiener lter is constructed by our algorithm using the estimated parameters and is then applied to the noisy wavelet coe cients at each scale We show that the averaged power spectrum of the denoised image is isotropic and is a near f process The performance of our algorithm is shown by numerical simulation for both the fractal parameter and the image estimation Applications on coastline detection and texture segmentation in noisy environment are also demonstrated EDICS number IP Address Institute of Information Science Academia Sinica Taiwan e mail whwang iis sinica edu tw
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Estimation of 2-D noisy fractional Brownian motion and its applications using wavelets
The two-dimensional (2-D) fractional Brownian motion (fBm) model is useful in describing natural scenes and textures. Most fractal estimation algorithms for 2-D isotropic fBm images are simple extensions of the one-dimensional (1-D) fBm estimation method. This method does not perform well when the image size is small (say, 32x32). We propose a new algorithm that estimates the fractal parameter ...
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