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基于特征选择的高光谱图像快速矢量量化算法

Fast VQ algorithm for hyperspectral image compression based on feature selection

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【作者】 陈雨时张晔谷延锋

【Author】 CHEN Yu-shi, ZHANG Ye, GU Yan-feng(Dept. of Information Engineering, Harbin Institute of Technology, Harbin 150001,China)

【机构】 哈尔滨工业大学信息工程系哈尔滨工业大学信息工程系 哈尔滨150001哈尔滨150001

【摘要】 高光谱图像在取得较高光谱分辨率的同时带来了海量数据,使其压缩成为必需.矢量量化技术在高光谱图像压缩中取得了良好效果,但有计算复杂度高的缺点.针对高光谱图像谱带间高度冗余的情况,本文提出基于特征选择的快速矢量量化算法.该算法在减少运算量同时,能取得和LBG算法相近的压缩效果.实验表明在信噪比略微下降的情况下,计算时间下降了94.32%.

【Abstract】 Hyper Spectral Image (HSI) can get fine spectral resolution as well as brings enormous data volume, so compression is necessary. Vector Quantization (VQ) can get good effect in HSI compression, but it has the shortcoming of computing expensively. By using of the fact that HSI has high redundancy in its bands, this paper proposed a feature selection based fast VQ algorithm. It has the advantage of being simple, producing a large computation time saving and yielding compression fidelity as good as the LBG algorithm. The experiment results showed that the runtime reduced 94.32% while the SNR slightly reduced by using our method.

【基金】 国家自然科学基金资助项目(60472048)
  • 【文献出处】 哈尔滨工业大学学报 ,Journal of Harbin Institute of Technology , 编辑部邮箱 ,2007年11期
  • 【分类号】TP751;TP391.41
  • 【被引频次】8
  • 【下载频次】222
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