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Vector quantizer of medical image using wavelet transform and enhanced neural network

机译:基于小波变换和增强神经网络的医学图像矢量量化

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Vector quantizer takes care of special image features like edges also and hence belongs to the class of quantizers known as second generation coders. This paper proposes a vector quantization using wavelet transform and enhanced SOM algorithm for medical image compression. We propose the enhanced self-organizing algorithm to improve the defects of SOM algorithm, which, at first, reflects the error between the winner node and the input vector to the weight adaptation by using the frequency of the winner node. Secondly, it adjusts the weight in proportion to the present weight change and the previous weight change as well. To reduce the blocking effect and Improve the resolution, we construct vectors by using wavelet transform and apply the enhanced SOM algorithm to them. Our experimental results show that the proposed method energizes the compression ratio and decompression ratio.
机译:矢量量化器还要照顾像边缘之类的特殊图像特征,因此属于称为第二代编码器的量化器类别。提出了一种基于小波变换和增强型SOM算法的医学图像压缩矢量量化方法。我们提出了一种改进的自组织算法来改善SOM算法的缺陷,该算法首先利用获胜者节点的频率将获胜者节点和输入向量之间的误差反映给权重自适应。其次,它根据当前的重量变化和先前的重量变化来调整重量。为了减少阻塞效应并提高分辨率,我们使用小波变换构造矢量,并将增强的SOM算法应用于矢量。我们的实验结果表明,该方法激励了压缩比和减压比。

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