Target Preserving Hyperspectral Image Compression Using Weighted PCA and JPEG2000

Lossy compression methods can significantly reduce the volume of hyperspectral images. Besides that, target detection performance degrades dramatically at lower bit-rates. In this paper, we propose a target preserving compression method for low bit-rates. The proposed method consists of three parts. In the first part, a target detection algorithm is performed on hyperspectral image. Afterwards, a weight matrix is generated using output of the target detection. Finally, Weighted Principal Component Analysis (WPCA) and JPEG2000 methods are executed sequentially. Two different approaches are proposed for weight matrix generation and the proposed approaches are compared with PCA+JPEG2000 and SubPCA+ JPEG2000 methods in terms of signal-to-noise ratio (SNR), receiver operating characteristic (ROC) curves and average mean square error. Experimental results demonstrate that WPCA+JPEG2000 provides significantly better target detection performance than other methods especially at low bit-rates.