Waveband-correlation-based intra-class local fitting and resorting method of remote sensing image

Abstract

The invention provides a waveband-correlation-based intra-class local fitting and resorting method of a remote sensing image. If the effective data of a local area of the remote sensing image on a certain waveband cannot be obtained due to data loss or noise disturbance, and the like, and the effective data is contained on a waveband adjacent to the spectral range of the waveband, then the effective data can be resorted through the correlation between the two wavebands. The method comprises the following steps of: carrying out unsupervised classification on several wavebands with stronger correlations so as to distinguish surface features with larger correlation differences among the wavebands; and then operating all points to be restored by adopting the intra-class local fitting and resorting method to obtain a restoring value. The invention restores a target image by sufficiently utilizing the correlations among a plurality of wavebands, takes surface feature types and spectral characteristics into considerations and can better approach to true data. Moreover, the invention has higher computing efficiency, easy realization and high practical value and is particularly suitable for restoring multi-waveband remote sensing image data.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and relates to a local fitting restoration method within a class of remote sensing images based on band correlation. Intact data to recover degraded or lost data on another related band. Background technique [0002] During the acquisition of remote sensing images, due to the influence of satellites, sensors, or the atmosphere, there may be some noise or data loss in the finally acquired images, which will affect the normal use of remote sensing images. Therefore, after the remote sensing image is acquired, it has become a very important subject to use technical means to correct and restore it. [0003] Commonly used image restoration methods can be divided into two types based on a single image and based on multiple images. Among them, restoration methods based on a single image include interpolation, histogram matching, moment matching, space-frequency domain filtering...

AI Technical Summary

Problems solved by technology

For the restoration method based on a single image, when the image loses too much information, it is difficult to obtain better results by restoring the remaining information in one image alone, and it is necessary to introduce information from another image.

However, the same ground object in different images will be affected by its own spectral characteristics, different image acquisition time and atmospheric factors, resulting in differences in imaging. This is a problem that must be considered in the restoration process, so it is necessary to study new methods. Methods

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