LBG Algorithm for Hyperspectral Remote Sensing Image Compression
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Resource Overview
The LBG algorithm for hyperspectral remote sensing image compression is a classic approach with robust implementation characteristics.
Detailed Documentation
The text discusses the LBG algorithm for hyperspectral remote sensing image compression, which represents a fundamental and widely-recognized methodology in the field. Hyperspectral remote sensing image compression serves as a crucial technique in remote sensing image processing, effectively reducing data volume while preserving essential information. The LBG algorithm operates as a vector quantization-based compression method that achieves image compression through pixel clustering and encoding processes. Implementation typically involves initial codebook generation followed by iterative clustering using distortion measures, where key functions include centroid calculation and codebook optimization. This algorithm has gained extensive application in hyperspectral remote sensing image processing and has demonstrated significant effectiveness in practical scenarios.
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