Image detail enhancement method of infrared image

Abstract

The embodiment of the invention discloses an image detail enhancement method of an infrared image. The image detail enhancement method of the infrared image includes the steps that an original infrared image is acquired; the original infrared image is de-noised; the de-noised infrared image is decomposed into a detail partial image and a base partial image; the detail partial image is processed through detail enhancement; the dynamic range of the base partial image is compressed; the detail partial image and the base partial image are synthesized, and a synthetic infrared image is obtained. According to the image detail enhancement method of the infrared image, on the basis of effectively suppressing noise, the scene information of the global large dynamic range is reasonably compressed, not only is the large dynamic range of the infrared image compressed, but also detail information of the infrared image is kept, and thus the visual effect of the whole image is obviously improved.

Description

technical field [0001] The invention relates to the technical field of infrared imaging, in particular to an image detail enhancement method of an infrared image. Background technique [0002] In short, infrared thermal imaging technology is to convert the infrared temperature signal radiated by the measured object into electrical signals of different intensities, and finally convert the electrical signals into video signals and input them to the terminal display device for display. In recent years, with the increasing maturity of uncooled focal plane array (UFPA) infrared detectors, thermal imaging technology has become more and more widely used in public security, fire protection, military, medical, power industry and other fields. Came into being. [0003] Since the infrared focal plane array thermal imaging system is an imaging of the temperature difference of the scene, the infrared thermal image represents the temperature distribution of the scene, which is a grayscal...

AI Technical Summary

Problems solved by technology

However, the general histogram equalization enhancement algorithm is not suitable for infrared image enhancement

In order to overcome the shortcomings of the histogram equalization algorithm, people proposed the histogram projection and platform histogram algorithm. Among them, for the platform histogram algorithm, the key to realize the algorithm is the selection of the platform value, but there is no selection platform threshold. The reasonable criterion is to select the platform threshold based on experience; while the histogram projection algorithm only distributes the gray levels appearing in the image at equal intervals in the entire gray space, and performs the same processing on the background noise and the target, and enhances the image. not effectively

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