SAR image denoising based on wavelet-fractal analysis

Wavelet-fractal based SAR (synthetic aperture radar) image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image. The method to denoise SAR image using the process based on wavelet-fractal analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hölder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.