Method for removing super-high-density salt-and-pepper noises of image

Abstract

The invention discloses a method for removing super-high-density salt-and-pepper noises of an image, and mainly at solving the problem that a present method cannot be used to filter super-high-density salt-and-pepper noises. The method comprises the realization steps that (1) an extremum method is used to detect noise points; (2) values of the noise points are substituted by the mean value of non-noise points of a four-point template in a 3*3 window, recursion is carried out for three times, values of the noise points are substituted by the mean value of non-noise points of a crossing template in the 3*3 window, recursion is carried out for three times, whether all the noise points are processed is determined after each time of recursion, if no, the window is increased, and the four-point template and the crossing template are used for identical recursion mean value filtering till a 11*11 window is reached; and (3) if the noise density is greater than 0.85, a 3*3 crossing window or a full-domain window is used to continue mean value filtering, and the super-high-density noises are removed. The method of the invention has the advantages of low computing complexity, large noise removing range, and capable of inhibiting the super-high-density salt-and-pepper noises effectively.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for reducing ultra-high-density salt-and-pepper noise in images that can be used in the fields of industrial images, agricultural images, medical images, and astronomical images. Background technique [0002] More than 50% of the pixels in the image with high salt and pepper noise are polluted by salt and pepper noise, and the noise level exceeds the range that conventional filtering algorithms in machine vision can handle. The traditional point of view is that: as a nonlinear filter, the median filter has the ability to filter salt and pepper noise and retain image details, and is one of the most suitable algorithms for image filtering with high salt and pepper noise in conventional filtering algorithms. On the basis of value filtering, some median filtering algorithms for high salt and pepper noise images are proposed. EsakkirajanS et al. proposed...

AI Technical Summary

Problems solved by technology

These improved methods improve the effect of removing salt and pepper noise, but the experimental results show that: for more than 90% of the pixels are polluted by ultra-high density salt and pepper noise, the denoising effect of these methods is not ideal

Other common denoising methods include methods based on Markov field models and partial differential equations, wavelet domain methods, principal component methods, and geometric scale analysis methods, etc., but some of these methods fail when dealing with ultra-high-density noise. , some calculation complexity is extremely high, it is difficult to apply

Images