目的 近年来随着光谱成像技术的快速发展,使得高光谱遥感图像能够提供更加丰富的地物信息,然而其所具有的极大数据量给图像的存储、传输和实用带来较大的困难。因此,如何对高光谱遥感图像进行有效编码成为研究热点。方法 基于陪集码的分布式信源编码因其具有良好的压缩性能和较低的编码复杂度而受到重视,在此基础上提出一种基于自适应四叉树分块的高光谱图像分布式无损编码方案。设每个高光谱帧组的第1帧为关键帧,其他帧为普通帧,首先对关键帧进行自适应四叉树分块,然后对每一块与普通帧相应的块进行最佳线性预测,进而根据预测残差确定所需传输的陪集码索引位数以及每个像素的k个最低比特位。结果 本文通过自适应四叉树分块,增强了所形成陪集码的自适应性。所提出的编码方案很好地实现了压缩效果和编码效率的折中。结论 提出的方案能够较好地适应低复杂度环境下对高光谱图像无损编码的需求。

Objective With the rapid development of spectral imaging technology in recent years, hyperspectral remote sensing images can provide abundant data on surface features. However,the sizable data of hyperspectral images make their storage, transmittal, and application quite difficult. As a result, how to validly code hyperspectral images has become a hot issue. Method The distributed source coding based on coset codes has received much attention because of its good compression performance and low coding complexity. In this study,we present a scheme for lossless distributed source coding of hyperspectral images based on adaptive quadtree segmentation. Assuming that the first frame in every group of spectrum frames is the key frame, the other frames are Wyner-Ziv frames. First, we perform adaptive quadtree segmentation on the key frame and then optimum linear prediction on each block of each Wyner-Ziv frame. Afterwards, the index of the coset codes to be transferred and the k least significant bits of every pixel in this block are ascertained using prediction residuals. Result In this study, adaptive quadtree segmentation scheme has been proved to strengthen the adaptability of the formed coset codes. The proposed scheme can achieve a good compromise between coding efficiency and calculating complexity. Conclusion This scheme is better able to meet the lossless coding requirement for hyperspectral images under low-complexity environment.