Effective compression of hyperspectral images is of great significance for real-time transmission. In this paper, spectral linear decomposition is introduced into efficient compression of hyperspectral image. According to the Linear Mixed Model(LMM), the hyperspectral data is decomposed into the product of endmember and abundance. At the encoder, the necessary data processing is performed on the endmembers and abundance, followed by JPEG-LS lossless compression. At the decoder, the original hyperspectral image is reconstructed by multiplying the final decoded endmembers and abundance, moreover, the effect of the quantization step on the rate-distortion performance is discussed. Experimental results show that the proposed method can achieve certain compression performance.