A PCA based fast vector quantization coding method for spectral imagery

In this paper, a PCA (Principal Component Analysis) based fast vector quantization coding method for spectral imagery has been proposed. Firstly, PCA is used to concentrate effective information of image into a few PCs (Principal Components). Then a PC selected method based on the eigenvalues is used to extract the PCs that contain the main information. Furthermore, an improved fast vector quantization (VQ) algorithm is exploited to encode the selected PCs. Experimental results show that, under the same coding conditions, the proposed method can achieve 13–16 dB higher reconstruction quality than JPEG2000 image coding standard.