Noise space characteristic based nonlinear filter denoising method

Abstract

The invention discloses a noise space characteristic based nonlinear filter denoising method, which comprises the following processes of: (1) inputting an image f detected by an infrared imaging detector; (2) establishing an image g which has the same size as that of the image f and has gray value of 0; (3) performing single-point denoising on the image f with noise; (4) performing two-point denoising on the image f with noise; (5) performing three-point denoising on the image f with noise; and (6) taking the gray value of a pixel, of which the gray value is zero and which is amended through the single-point denoising, the two-point denoising and the three-point denoising, in the image g as the gray value of the point in the image f. By adopting the method, blindness during denoising of the conventional nonlinear filter denoising method is made up, and difference of the noise space characteristic and the target space characteristic is fully utilized, so that detail and edge of the image can be kept well during denoising, and subsequent works such as image correction, target identification and the like are facilitated.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a nonlinear filter denoising method based on noise space characteristics. Background technique [0002] Images are often polluted by noise during formation, transmission and storage. The intensity of noise is generally defined by signal-to-noise ratio (snr) or decibel number (dB). The signal-to-noise ratio is the power ratio of the signal and noise in the image, and the conversion relationship between the signal-to-noise ratio and the decibel number is: [0003] dB=10log 10 snr [0004] Generally, the noise is randomly distributed in the image, and the support domain is small. Therefore, the traditional denoising method is to use a nonlinear median filter to filter the image to remove the noise with a small support domain in the image, so as to realize the denoising of the image. [0005] For weak noise in general, traditional filtering and denoi...

AI Technical Summary

Problems solved by technology

Using the traditional nonlinear filter denoising method to denoise the spatial target image will lose the details of the image while removing the noise, making the image more blurred and increasing the difficulty of subsequent processing (such as image correction, target recognition, etc.)

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