In this world of big data, the development and exploitation of medical technology is vastly
increasing and especially in big biomedical imaging modalities available across medicine …

Hyperspectral image compressive sensing reconstruction (HSI-CSR) is an important issue in
remote sensing, and has recently been investigated increasingly by the sparsity prior based …

Memory management and coding complexity are the major challenging issues of any
hyperspectral image sensor. The hyperspectral image compression algorithm plays a …

The 3D-zero memory set partitioned embedded block (3D-ZM-SPECK) is an embedded and
memory-efficient compression algorithm. Through, the 3D-ZM-SPECK does not require any …

Recent research has shown that spatial-spectral information can help to improve the
classification of hyperspectral images (HSIs). Therefore, three-dimensional convolutional …

Tucker decomposition (TD) is widely used in hyperspectral image (HSI) processing.
Generally, the performance of TD-based method depends on the core tensor and factor …

Remote sensing images provide a wealth of information for a variety of applications, but it is
at the expense of huge data. In this paper, we present a novel compression method based …

There is information redundancy in both spatial and spectral aspects of hyperspectral
images. Considering a fixed proportion in sequential forward method may not find the …

针对基于预测的高光谱图像无损压缩算法压缩比低的问题, 该文将聚类算法与高光谱图像预测
压缩算法相结合, 提出一种基于K-均值聚类和传统递归最小二乘法的高光谱图像无损压缩算法 …

With recent developments in ICT, the interest in using large amounts of accumulated data for
traffic policy planning has increased significantly. In recent years, data polishing has been …