Fast fusion system and fast fusion method for images

Abstract

The invention provides a fast fusion system and an implementing method for remote sensing images. The fusion system comprises an image preprocessing module, an image IHS (Intensity, Hue, Saturation) parallel fusion module, an image PCA (Principal Component Analysis) parallel fusion module, an image wavelet parallel fusion module and an image fusion effect parallel evaluation module. Both the image preprocessing module and the image fusion effect parallel evaluation module are connected with the image IHS parallel fusion module, the image PCA parallel fusion module and the image wavelet parallel fusion module. According to the fusion method, parallel fusion and evaluation are adopted. The invention provides the simple, convenient and efficient fast fusion implementing method for the remote sensing images, provides the efficient fast fusion method and implementing system for the remote sensing images for the remote sensing application in the fields of disaster prevention and relief, military and the like, and solves the problem of low fusion speed of the remote sensing images with large data volumes.

Description

technical field [0001] The invention relates to the technical field of information processing, in particular to an image parallel fusion method, in particular to a remote sensing image fast fusion system and an implementation method. Background technique [0002] Multi-sensor image fusion belongs to the category of multi-sensor information fusion. It refers to combining images of the same scene obtained by different sensors or images of the same scene obtained by the same sensor at different times according to a certain algorithm into an image that meets the given requirements. middle. Due to the limitations of the resolution limit determined by the energy and diffraction of light, the modulation transfer function of the imaging system, and the signal-to-noise ratio for a single sensor, it is difficult to simultaneously obtain high spectral, spatial, and temporal resolution. Multi-sensor image fusion technology can effectively use the complementary information and redundant...

AI Technical Summary

Problems solved by technology

(2) Lack of effective evaluation methods for data fusion results

Existing evaluation criteria are too simple, inflexible, and unable to adapt to the needs of technological development

(3) The traditional multi-source data association and fusion algorithm not only requires more prior knowledge, but also when the number of fusion sources increases and the number of sensors or objects to be observed increases, there will be a problem of N-P complete complexity in calculation. An insurmountable computational combinatorial explosion

(5) The fusion speed of large-scale remote sensing images is slow, and it is difficult to meet the application needs of some remote sensing fields

[0015] In short, at present, research on parallel program and algorithm design and image parallel processing is being carried out vigorously at home and abroad, but there are still few research results on parallel remote sensing image fusion.

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