文件名称:high-order-deconvlution
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- 上传时间:2012-11-16
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文件大小:2.95mb
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利用高阶谱进行系统辨识,估计得到点扩散函数,然后再进行傅域或小波域的解卷处理。由此得到的超声图像,分辨率大大提高了。-System identification using higher order spectrum, is estimated to be the point spread function, and then for Fu domain or wavelet domain deconvolution processing. The resulting ultrasound image, the resolution is greatly increased.
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基于高阶谱的解卷/Blind deconvolution through parametric identification using second and fourth order cumulants1996.pdf
基于高阶谱的解卷/higher Order Spectra Based Deconvolution of ultrasound image 1993 .pdf
基于高阶谱的解卷/IMAGE MODELING AND RESTORATION BY HIGHER-ORDER statistics based inverse filters.pdf
基于高阶谱的解卷/SSS Robust Deconvolution of High-Frequency Ultrasound Images Using Higher-Order Spectral Analysis and Wavelets 2003.pdf
基于高阶谱的解卷
基于高阶谱的解卷/higher Order Spectra Based Deconvolution of ultrasound image 1993 .pdf
基于高阶谱的解卷/IMAGE MODELING AND RESTORATION BY HIGHER-ORDER statistics based inverse filters.pdf
基于高阶谱的解卷/SSS Robust Deconvolution of High-Frequency Ultrasound Images Using Higher-Order Spectral Analysis and Wavelets 2003.pdf
基于高阶谱的解卷
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