Multispectral Image Compression Using Classification in Wavelet Domain and Classified Inter-channel Prediction and Selective Vector Quantization in Wavelet Domain

웨이브릿 영역에서의 영역분류와 대역간 예측 및 선택적 벡터 양자화를 이용한 다분광 화상데이타의 압축

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional method.