Hyperspectral image compressed coding method through multivariate vector quantization

Abstract

The invention relates to a hyperspectral image compressed coding method, in particular a hyperspectral image compressed coding method through multivariate vector quantization. The hyperspectral image compressed coding method through the multivariate vector quantization comprises the steps of reading hyperspectral image data; constructing a compression dictionary: according to two multivariate vector quantitative models and dictionary atom selection strategies, calculating dictionary atoms and coefficients of the dictionary atoms used by compression of each of picture elements by means of multiple regression; performing compressing and coding. According to the method, the vector quantitative models are reconstructed, two multivariate vector quantitative models are provided, the omitted error information is less than that in the traditional vector quantitative method, coefficients of the selected dictionary atoms are not defined in the newly-provided multivariate vector quantitative models, values of the coefficients are calculated out according to a spectrum and the dictionary, therefore, quality of the reconstructed images is ensured, and image distortion caused by compressed coding is reduced.

Description

technical field [0001] The invention relates to a hyperspectral image compression encoding method, in particular to a multivariate vector quantization hyperspectral image compression encoding method. Background technique [0002] As an important research direction of hyperspectral image processing, hyperspectral image compression coding technology has long been widely concerned by experts, scholars and engineers from various countries, and has been widely used in agriculture, mineral exploration, military defense and other fields. Hyperspectral images can provide a large amount of ground detail information by using imaging and spectral techniques. It can reflect the characteristics of ground objects in hundreds of electromagnetic spectrum bands. However, with the continuous development of hyperspectral technology, people's requirements for hyperspectral images are gradually increasing, which results in the continuous expansion of spatial and spectral resolution and the numb...

AI Technical Summary

Problems solved by technology

In the traditional vector quantization method, because the error is directly omitted, the compression will cause the degradation of the image quality that cannot be recovered, which will have a great impact on the subsequent image processing.

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