Fuzzy edge detection method based on object cloud

Abstract

The invention requests to protect a fuzzy edge detection method based on object clouds, which relates to a digital image processing technology. The method integrates the fuzzy set theory and the cloud theory to be applied in the image edge detection and designs a high efficient detection method which is applicable to the images, the object clouds are generated based on the gray features, a fuzzy object in the image is represented as the form of a could cluster, a normal cloud generator realizes the mapping of the image space and the cloud space, the cloud computing realizes the obtainment of the boundary cloud cluster and the digital features thereof, and the self-adaptive edge transition region processing is carried out according to the maximum fuzzy entropy principle; the method keeps the edge information of a great number of low gray values in the image, thus making up the shortcomings of the algorithm based on the fuzzy set theory to a great degree, taking into account of the problem of the randomness of uncertain boundary and being able to obtain good detection effect from the application in the multi-spectral image.

Description

Fuzzy edge detection method based on object cloud technical field The invention relates to digital image processing technology, in particular to image edge detection technology. Specifically, it is an image edge detection technology based on a new fuzzy theory - cloud theory. Background technique In recent years, people have done a lot of research on edge detection technology based on fuzzy theory, and many scholars at home and abroad are committed to introducing fuzzy theory into image processing. Such as S.K.Pal's fuzzy enhancement algorithm, T.L.Huntsberger's fuzzy C-means algorithm, fuzzy neural network algorithm, fuzzy competitive edge detection algorithm, etc. However, the existing fuzzy detection operators are not perfect. On the one hand, the detection effect is poor in the actual situation, especially when the image is noisy; on the other hand, it cannot be effectively applied to remote sensing image detection, especially For the multi-spectral images that are w...

AI Technical Summary

Problems solved by technology

However, the extraction of image details is still not particularly ideal, and the anti-noise performance is not very high

The general fuzzy algorithm based on fuzzy set theory uses an accurate membership function to describe a set of fuzzy edges, and artificially incorporates fuzzy concepts into the precise mathematical kingdom. The incompleteness of this traditional fuzzy set theory leads to the forced precision of fuzzy edges. This contradicts the fuzzy nature of remote sensing data

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