Hyperspectral Image Strip With Noise Elimination Research

Due to its various characteristics such as numerous bands, high spectral resolution and large amounts of data, hyperspectral remote sensing plays a more and more important role in both civil and military areas.However, because of the affection of various factors, hyperspectral images are usually seriously corrupted by stripe noises. The presence of stripe noises degrades the quality of hyperspectral images and brings huge inconvenience to the sequent image processing tasks. Therefore, destriping is one of the most important pre-processing steps in hyperspectral image processing. The research content is the reduction of stripe noises in hyperspectral images. The basic objective is to effectively remove stripe noises while preserving the original image details as much as possible so that the original radiation of various objects could be obtained better.Because stripe noises are widely imposed on hyperspectral images and far different from common noises, many scholars have studied on the destriping algorithms. However, there are still some problems and defections in the previous algorithms. In our research, we firstly analyzed the main causes and characteristics of stripe noises, then we proposed four new destriping algorithms based on previous algorithms.1. Proposed an adaptive glide-matching destriping algorithm, which is in spacial domain . It well integrated the spatial gliding filter ideas with matching ideas, which...