Hyperspectral image compression suitable for spectral analysis application

In the compression technique of hyperspectral image (HSI), PSNR of the reconstructed image is usually used for evaluating the performance of the coding results. For the spectral analysis applications of HSI, it is also important to consider the error in the result of spectral analysis. In the vegetation analysis, for example, the distortion of the vegetation index should be considered in addition to the distortion in the spectral data. This paper presents a HSI compression considering the error of both vegetation index and spectral data. The proposed method separates a hyperspectral data into spectral data for vegetation index and residual data. Both of the data are encoded by using a seamless coding individually. By holding the spectral channels required for vegetation index in the head of the code-stream, a precise vegetation analysis can be done in a low bit rate. Additionally, by decoding the residual data, the spectral data can be reconstructed in low distortion.