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An Image Compression Method Based on Wavelet Transform and Fuzzy SOFM Algorithm

机译:基于小波变换和模糊SOFM算法的图像压缩方法

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A fast and effective image compression method based on wavelet transform and neural network algorithm is proposed in this paper. Firstly, the image is decomposed by wavelet base and the input vector of neural network is formed. Secondly, we use fuzzy learning rule to train the SOFM network, obtain the codebook. This method can efficiently remove correlation in image date, obtaining a low transmission bit stream. The apparent advantage of the methods is to establish statistics codebooks for various image data and it can achieve a high coding efficiency because each treating need not generate codebook. Experiments illustrate that this algorithm is an effective encoding scheme to compress images and the compress ratio excels that of JPEG.
机译:本文提出了一种基于小波变换和神经网络算法的快速有效的图像压缩方法。首先,通过小波基分解图像,形成神经网络的输入向量。其次,我们使用模糊学习规则来训练SOFM网络,获取码本。该方法可以有效地去除图像日期中的相关性,获得低传输比特流。该方法的表观优点是为各种图像数据建立统计码本,并且可以实现高编码效率,因为每个治疗不需要生成码本。实验说明该算法是压缩图像的有效编码方案,并且压缩比率是JPEG的。

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