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首页> 外文期刊>Advances in Experimental Medicine and Biology >Medical image processing using novel wavelet filters based on atomic functions: Optimal medical image compression
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Medical image processing using novel wavelet filters based on atomic functions: Optimal medical image compression

机译：使用基于原子函数的新型小波滤波器进行医学图像处理：最佳医学图像压缩

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摘要

The analysis of different Wavelets including novel Wavelet families based on atomic functions are presented, especially for ultrasound (US) and mammography (MG) images compression. This way we are able to determine with what type of filters Wavelet works better in compression of such images. Key properties: Frequency response, approximation order, projection cosine, and Riesz bounds were determined and compared for the classic Wavelets W9/7 used in standard JPEG2000, Daubechies8, Symlet8, as well as for the complex Kravchenko-Rvachev Wavelets ψ(t) based on the atomic functions up(t), fup 2(t), and eup(t). The comparison results show significantly better performance of novel Wavelets that is justified by experiments and in study of key properties.
机译：提出了基于原子函数对不同小波的分析，包括新颖的小波家族，特别是针对超声（US）和乳腺摄影（MG）图像压缩。这样，我们就可以确定哪种类型的过滤器Wavelet在压缩此类图像时效果更好。关键特性：确定并比较了用于标准JPEG2000，Daubechies8，Symlet8以及基于Kravchenko-Rvachev小波ψ（t）的经典小波W9 / 7的频率响应，近似阶数，投影余弦和Riesz边界。关于原子函数up（t），fup 2（t）和eup（t）。比较结果表明，通过实验和关键特性的研究证明，新颖的小波具有更好的性能。

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