Research On Hyperspectral Remote Sensing Image Fusion And Quality Evaluation Method

Hyperspectral image is provided with the ability of detecting ground features accurately, as well as wide application foreground. The study on technique of processing and analyzing hyperspectral image is becoming a pop problem. However, the spatial resolution of hyperspectral image is restricted with being promoted, so only when fused with high spatial image, hyperspectral image could meet the needs for spatial position and attributes acquisition. Based on analyzing the study status of hyperspectrual image and high spatial image fusion, this dissertation lucubrates the method of fusion in the pixel level, improves the method of Non-negative Matrix Factorization (NMF) image fusion, devises the method of image fusion based on Genetic Algorithm (GA) and lucubrates the method of quality evaluation of fused images. The major works implemented are listed as follow:1.The characteristics of hyperspectral image data are summarized, the study status of remote sensing image fusion is analyzed and the importance of hyperspectral image fusion with the high spatial image is emphasized.2.Fusion methods in the pixel level are lucubrated, the matters and methods of preprocessing hyperspectral image are introduced, and the methods of hyperspectral image band selection based on information and classes distinguishability respectively are expatiated. On the basis that manifold methods of fusion in the pixel level are studied, implementation methods of these arithmetic are analyzed and virtue and defect of them are concluded.3.The existing subjective and objective quality evaluation methods of remote sensing image fusion are analyzed. In order to achieve the goal of comprehensive evaluation, fuzzy comprehensive evaluation is applied to the remote sensing image fusion quality evaluation and fuzzy comprehensive evaluation method of fusion images based on Analytic Hierarchy Process (AHP) is devised. Experiments show that it posses the characteristic of giving attention to subjective and objective factors, expressing in fix quantity and distinguishing virtues and defects easily, as well as evaluating accurately.4.Based on analysis of the principle and implementation of Non-negative Matrix Factorization (NMF), the image fusion method combined with IHS transform based on NMF is improved. Experiments on the multispectral and hyperspectral data indicate that the method in this dissertation possess virtues of getting over spectrum distortion and preserving image information, compared with the fusion methods in common use.5.The principle, flow and inscape of Genetic Algorithm(GA) are studied, the fusion method based on GA is devised. Contrast experiments show that the method is provided with characteristics of agility and obvious advantage of complementing information for each other.