A Registration Method of Visible and Infrared Images Based on Multi-scale Segmentation and SIFT

Abstract

The invention discloses a registration method for visible light and infrared images based on multi-scale segmentation and SIFT, which comprises the following steps: step 1, preprocessing is performed to visible light images and infrared images, wherein Gaussian filtering processing is performed to the visible light images, and linear enhancement processing is performed to the infrared images; step 2, an initial parameter value which includes a scale factor, a compact factor and a shape factor is set, and the multi-scale image segmentation is performed to the visual light and infrared images subjected to preprocessing; step 3, the SIFT registration is performed to the visible light and infrared images subjected to the multi-scale image segmentation, calculation parameters of homonymy point selection transformation models are found out and the registration is performed to source images; step 4 and step 5, judgment is performed, if the visible light images and the infrared images are not subjected to accurate registration or the registration accuracy does not meet the requirement of the set threshold, the operation is returned to step 2 to adjust the parameter value of the multi-scale image segmentation method till the registration accuracy of the visual light images and infrared images meets the requirement of the set threshold, iteration is stopped, and the registration result is output.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a method for registering visible light and infrared images based on multi-scale segmentation and SIFT. Background technique [0002] Image registration (ImageRegistration) technology is the process of spatially aligning images taken in the same area at different angles of view, at different times, with different sensors or under different lighting conditions. This technology is extremely critical in the process of heterogeneous spatial data acquisition and integration. Step, to find the best geometric transformation parameters is the ultimate goal of image registration. Visible light sensor has always been one of the important sensors in the field of remote sensing because of its very high image resolution and the image obtained is consistent with the human visual effect. However, visible light images are greatly affected by weather conditions such as clo...

AI Technical Summary

Problems solved by technology

However, due to the different imaging principles of the two types of images, there is a large difference in the gray level, so it is an effective method to extract feature information for image registration, but in most cases, the feature information extraction of the image is not accurate, which leads to There is a large error in the subsequent registration process, which requires some means to process the image before extracting the feature information of the heterogeneous image, such as image segmentation, so that it is easier to extract effective feature information from the two images

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