The linear prediction vector quantization for hyperspectral image compression
The linear prediction vector quantization for hyperspectral image compression is a scholarly work, published in 2018 in ''Multimedia Tools and Applications''. The main subjects of the publication include quantization, image compression, hyperspectral imaging, vector quantization, noise reduction, artificial intelligence, computer science, linear prediction, algorithm, correlation, pattern recognition, cluster analysis, and centroid. The experiments results using AVIRIS images are compared to IVQ and AR + SubPCA+JPEG2000 algorithm, the results show that the authors' proposed algorithm outperforms other algorithms.