Multi-level codebook vector quantitative method for compressed encoding of hyperspectral remote sensing image

The invention discloses a multi-level codebook vector quantitative method for compressed encoding of a hyperspectral remote sensing image and relates to the technical field of image processing. According to the method, a spectral vector of the hyperspectral image is divided into a low-dimension part, a middle-dimension part and a high-dimension part according to the distortion condition, then a large-size codebook is adopted in the low-dimension part with large distortion, a medium-size codebook is adopted in the middle-dimension part with not large distortion, a small-size codebook is adopted in the high-dimension part with small distortion, and therefore the multi-level codebooks are adopted, the mode that only a quarter of the weight training code index of the low-dimension part is extracted after dispersion degrees are ranked is combined, and the targets of effectively reducing the quantizing distortion of the hyperspectral image and obviously reducing calculation amounts of all parts are achieved with the same compression ratio. On the condition of the low calculation complexity, high-quality compressed encoding of the hyperspectral image is achieved with higher speed, and the method has the actual application value and is a hyperspectral image lossy and nearly lossless compression scheme good in compression performance.