一种基于预测和变换混合设计的超光谱图像压缩方法

提出了一种新的超光谱图像压缩方法。该方法针对三维小波压缩编码方法对专有数据的特殊属性利用效率较低的缺陷,设计了一种应用于超光谱图像的预测编码和变换编码相混合的实现方案。首先,由超光谱图像的高谱间相关性,推导出图像各波段间的一般表达式。然后,根据这一表达式建立了超光谱图像的波段预测方式。该预测方式以波段为单位,参考波段采用小波变换编码技术进行压缩。为了提高预测的精度,参考波段选择器和波段预测器分别基于超光谱图像的数学统计规律和各波段直方图形状相似的特性进行设计。最后,将预测偏差值通过三维小波编码技术进行压缩。实验结果表明,本文设计的方法与目前先进的超光谱压缩技术相比能够提供具有竞争力的性能提升,且具有良好的兼容性、灵活性和渐进传输能力。

A Hyperspectral Image Compression Method Based oil Hybrid Predictive Coding and Transflorm Coding

In this article a new hyperspectral image compression method is proposed. Since the three-dimensional wavelet transform compression cannot efficiently utilize the properties of a certain class of images, a hybrid predictive coding and transform coding scheme for hyperspectral images is designed. First, a general expression is derived from the high spectral correlation of hyperspectral images. Then, a new band prediction mode is built in accordance with the expression. Based on the mode all the spectral bands of a hyperspectral image can be reconstructed from a reference band compressed by wavelet transform coding. To improve the precision of prediction, the selector of the reference band and the predictor are established according to the statistical regularity of hyperspectral images and the property of similarity that exists among the shapes of histograms of most bands in the image. Finally, deviation data of the band prediction are compressed by three-dimensional wavelet transform coding. Results indicate that the proposed method can provide competitive performance in comparison with the state-of-the-art technique and it possesses such advantages as good scalability, high flexibility and good progressive transmitting capability.