Image median filtering method based on incomplete rapid sorting algorithm

Abstract

The invention relates to an image median filtering method based on an incomplete rapid sorting algorithm. The image median filtering method includes the following specific steps that according to a row-major sequence or a line-major sequence, all pixels of an image are scanned and all pixels in a certain neighbourhood of a target pixel of the image are obtained; an element in the sequence is randomly selected as a pivot point, assuming that the position of the pivot point after one-time scanning processing is changed to be m, all the elements which are in an image pixel sequence and are smaller than the pivot point value are moved to be in front of the pivot point and all the elements which are in the image pixel sequence and are larger than the pivot point value are moved to be in rear of the pivot point, and an original sequence is divided into two parts; the position of the pivot point is judged after rapid sorting, if the position of the pivot point is just the middle position of the sequence, a k value is obtained, the K value is used for replacing the value of the image target pixel, and the process is terminated; otherwise, according to the size relation between m and k, a proper subsequence is chosen to repeat the process. According to the image median filtering method based on the incomplete rapid sorting algorithm, a large amount of data sorting and time-consuming data moving operation is reduced and the processing speed is greatly improved when the processing precision is ensured.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image median filtering method based on an incomplete quick sorting algorithm. Background technique [0002] Noise filtering is an important step and link in digital image preprocessing, and its performance and speed directly affect subsequent processing. Images may be polluted to varying degrees during the process of acquisition, transmission, transformation, storage, etc., resulting in degradation of image quality. Currently popular noise filtering methods can be divided into two categories: linear algorithms and nonlinear algorithms. Linear algorithms often have low-pass characteristics, while image contours, edges, and textures belong to high-frequency parts, so linear filtering algorithms will blur the image and affect the visual effect. [0003] As a typical nonlinear filtering algorithm, the median filtering algorithm can retain edge information, contour information and...

AI Technical Summary

Problems solved by technology

[0004] Among many fast algorithms, except for the difference insertion sorting method, other fast algorithm methods have certain errors, and the calculated median value is not necessarily the theoretical median value of all pixels in the neighborhood, which may degrade the image quality , causing certain distortion and affecting the visual effect of the image

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