Intelligent infrared image scene enhancing method

Abstract

The invention provides an intelligent infrared image scene enhancing method comprising the following steps: using an improved combined double-side filter to make combined calculation for two adjacentinfrared images, thus obtaining a detail layer component and a fundamental frequency layer component of a reference frame image; using a guiding gray scale similarity item kernel function to control the detail layer component enhancing scope and eliminate an edge gradient overturn effect, and using an improved histogram calculating method to control the grey scale redistribution of the whole imagein the fundamental frequency layer component; stacking and restoring the processed detail layer image and the fundamental frequency layer component, thus enhancing the original reference frame infrared image scenes. The method can effectively solve the problems that a normal infrared image detail enhancing method effect is too abrupt, so the processed infrared image can have an excellent scene detail enhancing ability; in addition, the grey scale distribution can approach to real scenes in a higher level, thus greatly improving the infrared image visual impressions.

Description

technical field [0001] The invention relates to the technical field of infrared image high dynamic range display, in particular to an intelligent infrared image scene enhancement method. Background technique [0002] Infrared thermal imaging is widely used in military and civilian fields, such as system design, system testing, system manufacturing, chemical imaging, night vision imaging, disaster search and rescue, target recognition and detection, and target tracking. Generally, ordinary infrared cameras have a very wide dynamic range of data, and traditional display devices do not support such a high dynamic range, so when displaying infrared images, the common method is to perform a similar histogram on the infrared image Equalization and other high dynamic range compression techniques. However, the simple histogram equalization technology has extremely limited effect on improving the visual perception of infrared images, and cannot fully express the details in the real ...

AI Technical Summary

Problems solved by technology

In order to overcome this problem, some researchers used Gaussian filters to process strong edges, but due to the incomplete matching of the mathematical model, this "ghost" could not be completely eliminated, which greatly reduced its application in actual engineering. The latter uses a guided linear filter, although it can obtain a good "ghost" elimination effect, but due to the computational efficiency constraints of the linear filter, the final image enhancement effect is average, and it cannot fully highlight all the ghost images in the scene. Small details also limit its application effect in actual engineering

So until now, in the infrared thermal imaging system, there has not been an excellent scene detail enhancement algorithm applied to the engineering machine

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