Method and device for fusing infrared and visible light images based on spectral wavelet transformation

Abstract

The invention discloses a method and a device for fusing infrared and visible light images based on spectral wavelet transformation. The method comprises the steps of performing spectral wavelet decomposition on an infrared image and a visible light image according to four decomposition scales to obtain a low-frequency sub-band coefficient and high-frequency sub-band coefficients, fusing the obtained low-frequency sub-band coefficient and the high-frequency sub-band coefficients at different decomposition scales according to a fusion rule, and performing spectral wavelet transformation on the fused low-frequency sub-band coefficient and high-frequency sub-band coefficients to obtain a fused image. The invention also discloses a device for fusing infrared and visible light images based on spectral wavelet transformation. According to the method and the device for fusing infrared and visible light images based on spectral wavelet transformation, the images of irregular images can be expressed better; a weight of image fusion is obtained by virtue of bilateral filtering so that the definition, the contrast ratio, the amount of information and the like of the fused image can be effectively improved, and consequently, a better-fused image can be obtained.

Description

technical field [0001] The invention belongs to the technical field of image fusion processing, and in particular relates to an infrared and visible light image fusion method and device thereof based on spectrogram wavelet transform. Background technique [0002] Image fusion is of great significance in image analysis and computer vision. Through image fusion technology, images of the same scene acquired from different imaging sensors can be organically combined into one image, which can effectively complement the advantages of images acquired by different imaging sensors, and form an image that can truly and clearly reflect the objective scene, so that image Further analysis, understanding, detection and identification of targets, etc. [0003] Since the 1980s, multi-sensor image fusion has aroused widespread interest and research upsurge, and it has broad application prospects in machine learning, remote sensing, computer vision, medical image processing, and military app...

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Problems solved by technology

However, NSCT also has its own shortcomings: since the direction filter used by NSCT is a non-subsampling filter bank of fan-shaped filter, the band-pass direction sub-band coefficients are obtained through this filter; thus, the calculation amount of the image fusion method based on NSCT is relatively large. Large, not conducive to practical application

In view of the above advantages of NSST, scholars have introduced NSST theory into image fusion, see the article "Technique for gray-scale visual light and infrared image fusion based on non-subsampled shearlet transform", Infrared Physics & Technology, 2014, 63:110 -118; This method fuses the low-frequency sub-band coefficients and high-frequency sub-band coefficients obtained by NSST decomposition respectively using the fusion rules of regional energy mean and local direction contrast, and the obtained fusion image is clearer than the fusion image obtained based on NSCT The brightness and spatial activity have improved, but the amount of information and contrast are still relatively low, and the overall effect is still unsatisfactory

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