Infrared and low-light image fusion method based on edge information and support transformation

Abstract

The invention discloses an infrared and low-light image fusion method based on marginal information and support degree transformation. The method includes the steps of conducting marginal detection on source images at the first time, fusing the results obtained through detection to obtain a first-time fused image, conducting multi-scale decomposition on the two source images and the first-time fused image through the SVT at the second time so as to obtain all scales of approximate images and all scales of support degree images of the source images and the first-time fused image, fusing all scales of support degree images according to the fusion strategy of local energy to obtain a support degree fused image of the two source images, conducting weight fusion on the support degree fused image of the two source images and all scales of support degree images obtained through the decomposition of the first-time fused image so as to obtain the final support degree fused image, conducting support degree inverse transformation on the fused approximate images and the final support degree image, and conducting reconstruction to obtain the final fused image. By means of the method, the efficient image fusion can be conducted on infrared and low-light images.

Description

technical field [0001] The invention belongs to the technical field of image fusion, in particular to an infrared and low-light image fusion method based on edge information and support transformation. Background technique [0002] As Li Caiping, Zou Yongxing and Yang Songling mentioned in the article "Night Vision Technology Based on Low-light and Infrared" published in the second issue of foreign electronic components in 2006, a single infrared or low-light imaging technology has its own advantages and disadvantages due to different principles. pros and cons. Low-light images have poor contrast, limited gray scale, poor instantaneous dynamic range, flicker at high gain, and are only sensitive to the reflection of the target scene, regardless of the thermal contrast of the target background. The contrast of the infrared image is poor, and the dynamic range is large, but it is only sensitive to the radiation of the target scene, but not sensitive to the brightness change of...

AI Technical Summary

Problems solved by technology

Poor low-light image contrast, limited gray scale, poor instantaneous dynamic range, flicker at high gain, only sensitive to reflections of target scene, not related to thermal contrast of target background

The infrared image has poor contrast and a large dynamic range, but it is only sensitive to the radiation of the target scene, but not sensitive to the brightness change of the scene

Both have deficiencies. With the development of low-light and infrared imaging technology, it has become an effective technical means to synthesize and explore the feature information of low-light and infrared images, so that they can be fused into a more comprehensive image.

Images