Hyperspectral Data Compression provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery.Chapter 1 addresses compression architecture, and reviews and compares compression methods. Chapters 2 through 4 focus on lossless compression (where the decompressed image must be bit for bit identical to the original).Chapter 5, contributed by the editors, describes a lossless algorithm based on vector quantization with extensions to near lossless and possibly lossy compression for efficient browning and pure pixel classification.Chapter 6 deals with near lossless compression while. Chapter 7 considers lossy techniques constrained by almost perfect classification. Chapters 8 through 12 address lossy compression of hyperspectral imagery, where there is a tradeoff between compression achieved and the quality of the decompressed image.Chapter 13 examines artifacts that can arise from lossy compression.
Recommendations
Spectral distortion in lossy compression of hyperspectral data
Distortion allocation varying with wavelength in lossy compression of hyperspectral imagery is investigated, with the aim of minimizing the spectral distortion between original and decompressed data. The absolute angular error, or spectral angle mapper (...
Lossy Hyperspectral Image Compression Based on Intraband Prediction and Inter-band Fractal
ICEMIS '18: Proceedings of the Fourth International Conference on Engineering & MIS 2018Fractal encoding promising proficiency in area of picture compressing but not used at compression of hyperspectral images. The paper presents a novel and applicable copy hyperspectral image lossy compressing founded in intra-prediction fractals ...