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作 者:Zhao Jian Cao Zhengwen Zhou Mingquan
机构地区:[1]School of Electronics and Information, Northwestern Polytechnical Univ., Xi'an 710072, E R. China [2]School of Information Science and Technology, Northwest Univ., Xi'an 710069, E R. China
出 处:《Journal of Systems Engineering and Electronics》2007年第1期45-48,共4页系统工程与电子技术(英文版)
摘 要: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-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder 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.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-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder 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.
关 键 词:Synthetic aperture radar image WAVELET Multifractal analysis DENOISING Hoelder exponent
分 类 号:TN957.52[电子电信—信号与信息处理] TN957.54[电子电信—信息与通信工程]
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