Self-adaptive median filtering denoising method applied to image processing

An image processing, filtering and denoising technology, applied in image data processing, image enhancement, instruments, etc., can solve the problems of fixed filter window size, high time complexity, and no consideration of algorithm complexity and time-consuming. Improved recognition rate and good denoising performance

Pending Publication Date: 2019-05-17
CENTRAL SOUTH UNIVERSITY OF FORESTRY AND TECHNOLOGY
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AI Technical Summary

Problems solved by technology

The adaptive filtering algorithm based on recursive least squares RLS (Recursive of Least Square) has the characteristics of good denoising performance and high precision. effect, but none of them considered the problem of high algorithm complexity and extremely time-consuming
And in recent years, with the development of artificial intelligence technology, advanced machine learning algorithms such as convolutional neural network and support vector machine (SVM) have been well applied in the field of image recognition. No attempt was made to preprocess the raw image input to the model
[0004] Therefore, in view of the fact that most of the traditional median filtering algorithms use bubble sorting, the time complexity is high, and the size of the filter window is fixed, it cannot take into account both denoising and image detail protection at the same time. Combined Captcha Recognition Method

Method used

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  • Self-adaptive median filtering denoising method applied to image processing
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  • Self-adaptive median filtering denoising method applied to image processing

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Embodiment 1

[0063] Step 1: Quick Sort Combined with Data Dependency

[0064] The divide and conquer method quickly sorts the data, that is, sorts the data in blocks, divides the data into several blocks according to the set benchmark elements and sorts them separately, and then merges the sorting results of each block to obtain the final sorting result . Compared with the traditional sorting algorithm, the divide-and-conquer idea of ​​fast sorting achieves the effect of parallel sorting of each block, which can greatly reduce the complexity of sorting and improve the efficiency of filtering.

[0065] The basic idea of ​​the divide-and-conquer quick sort algorithm is: for the array to be sorted is A[0]...A[N-1] first find a reference element to perform a quick sort, so that all the data on the left of the reference element It is small, and all the data on the right are larger than it, and then according to this method, the data on the left and right sides are quickly sorted, and the entir...

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Abstract

The invention discloses a self-adaptive median filtering denoising method applied to image processing, which comprises the following steps of: firstly preprocessing an image, and then, (1) sorting data in a filtering window by adopting a divide-and-conquer sorting strategy; And (2) adaptively adjusting the size of a filtering window by combining the noise density. The adaptive median filtering denoising method applied to image processing is high in denoising efficiency and easy to implement.

Description

technical field [0001] The invention relates to an adaptive median filter denoising method applied to image processing. Background technique [0002] The development of verification code recognition technology not only facilitates users to obtain massive information, but also promotes the development of image processing, pattern recognition and other technologies. Image denoising is an important link in the verification code recognition technology, and the present invention analyzes the image denoising algorithm by taking the image verification code as the research object. With the generation and development of image processing technology, image denoising algorithm has formed a relatively complete algorithm technology system. The proposal of the mean value denoising algorithm has led to the vigorous development of the traditional linear denoising algorithm. However, this type of algorithm will blur the details of the image while removing the noise, so it is quickly replaced...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 秦姣华马文涛向旭宇谭云
Owner CENTRAL SOUTH UNIVERSITY OF FORESTRY AND TECHNOLOGY
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