本文根据高光谱图像具有空间和谱间相关性的特点,提出一种基于三维整型DCT变换的无损压缩方法。首先采用三维整型DCT变换消除高光谱图像空间和谱间的相关性;然后,对变换系数进行类似小波的树状系数重组,并按子带顺序进行一阶自适应算术编码。实验结果表明,本文提出的方法与JPEG2000中无损压缩算法相比,平均比特率降低0.1~0.4bpp;与JPEG-LS相比,平均比特率降低0.01~0.2bpp。
This paper presents a three-dimension integer reversible DCT scheme to compress the data losslessly according to the characteristic of hyperspectral data. First, the data are decorrelated spatially and spectrally using three-dimension integer DCT method, then DCT-based coefficients-reordering and Zigzag scanning by subbands are applied to improve the coding efficiency before the context-based adaptive arithmetic coding (AAC). Experiments show that the performance of the present method is evident: 0.1-0.4bpp is saved with respect to JPEG2000, and 0.01-0.2bpp is saved with respect to JPEG-LS on average.