Remote sensing image fusion quality evaluation method

Abstract

The invention discloses a remote sensing image fusion quality evaluation method, which comprises the steps of extracting LBP feature statistical histograms, edge histograms and spectral features of sub-blocks in different waveband images as feature vectors, and constructing an original multivariate Gaussian model in a training stage; in the test stage, constructing original multivariate Gaussian models in the test stage, and calculating a full-resolution quality evaluation prediction value according to the two original multivariate Gaussian models constructed during training and testing; calculating spectral similarity and spatial similarity between all waveband images of the multispectral image referred by the test remote sensing fusion image and downsampling waveband images obtained after downsampling operation is carried out on all waveband images of the test remote sensing fusion image, and obtaining a resolution reduction quality evaluation prediction value; and obtaining an objective quality evaluation prediction value. Due to the fact that the obtained feature vector information can well reflect the quality change condition of the remote sensing fusion image, the correlationbetween an objective evaluation result and human eye subjective perception is effectively improved.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to a remote sensing image fusion quality evaluation method. Background technique [0002] Panchromatic multispectral fusion is a research hotspot in the field of remote sensing image fusion. Multispectral images usually have low spatial resolution, while panchromatic images usually have high spatial resolution but lack spectral information. The purpose of panchromatic multispectral fusion is to fuse the spatial information of panchromatic images into multispectral images to obtain multispectral images with high spatial resolution. However, different fusion methods have different fusion effects on different panchromatic images and multispectral images. How to evaluate the quality of the fused images is a technical problem that needs to be solved at present. [0003] At present, in the field of panchromatic multispectral fusion image quality assessment, there are mainly the foll...

AI Technical Summary

Problems solved by technology

However, different fusion methods have different fusion effects on different panchromatic images and multispectral images. How to evaluate the quality of the fused image is a technical problem that needs to be solved at present.

Images