Infrared image hybrid noise reduction method based on noise recognition

Abstract

The invention discloses an infrared image hybrid noise reduction method based on noise recognition, which comprises the following steps: firstly, carrying out 3 * 3 median filtering on a near-infrared image by using a filter to obtain an image only containing Gaussian noise, and then carrying out wavelet transform denoising processing on the image; secondly, after wave decomposition, main information of the image being almost all distributed in a low-frequency sub-band, and processing of a low-frequency part being often omitted in order to prevent important information from being damaged during denoising; performing thresholding processing on the wavelet coefficient of the high-frequency region after image decomposition, and then performing median filtering again by adopting a 5 * 5 filter; and finally, performing wavelet reconstruction by using the wavelet coefficient of each sub-band to obtain a denoised image. Through the above mode, compared with a single denoising method, the hybrid noise reduction method can more effectively remove noise and improve the signal-to-noise ratio of the near-infrared face image in view of the denoising effect of the collected night infrared image, and edge details of the image are well reserved.

Description

technical field [0001] The invention relates to the technical field of infrared image processing, in particular to an infrared image hybrid noise reduction method based on noise recognition. Background technique [0002] In the visible light environment, the illumination seriously affects the positioning of the eyes. Even at night, it is difficult to accurately detect the face area, let alone accurately locate the eyes. Near-infrared light basically does not have the limitations of natural light, and can be absorbed by the pupil, while a lot of it is reflected by the iris. Use the difference between them to quickly detect human eyes and achieve real-time facial monitoring. However, due to the influence of the converted device and the environment on the captured image, the image acquired in the computer contains infrared noise such as Gaussian and salt and pepper, which leads to partial distortion of the image. In order to obtain near-infrared facial images with high signal...

AI Technical Summary

Problems solved by technology

However, due to the influence of the acquired image through the conversion device and the environment, the image acquired in the computer contains infrared noise such as Gaussian and salt and pepper, which leads to partial distortion of the image.

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