A Weak Edge Detection Method for Multi-Scale Images Based on Minimum Description Length

A detection method and weak edge technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problem of lack of scale selection criteria for algorithms

Active Publication Date: 2016-09-07
SUN YAT SEN UNIV
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Problems solved by technology

[0010] Aiming at the lack of reasonable scale selection standards in existing algorithms, the present invention determines an optimal local scale calculation standard. In view of this standard, a local multi-scale adaptive image weak edge detection method based on the minimum description length principle is proposed. it includes:

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  • A Weak Edge Detection Method for Multi-Scale Images Based on Minimum Description Length
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  • A Weak Edge Detection Method for Multi-Scale Images Based on Minimum Description Length

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Embodiment Construction

[0083] The present invention will be further elaborated below in conjunction with the accompanying drawings.

[0084] Such as figure 1 As shown, the traditional Canny operator includes the following four basic steps:

[0085] (1) Smoothing: suppress noise as much as possible without destroying real edges.

[0086] (2) Differentiation (Gradient): apply the differential operator to find the gradient of the smooth image, and use it as an indicator of marginality.

[0087] (3) Detection: To judge which edge pixels should be removed as noise and which ones must be kept, the threshold method is usually used as the criterion.

[0088] (4) Localization: determine the exact position of the edge (in some special occasions, localization should reach sub-pixel resolution, such as satellite maps and visual measurement).

[0089] (5) Thinning and linking: maintain the single-pixel characteristics and integrity of the edge.

[0090] In view of the high complexity of the existing algorith...

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Abstract

The invention discloses a self-adaptive multi-scale image weak edge detection method based on the minimum description length (MDL) principle. The self-adaptive multi-scale image weak edge detection method based on the minimum description length principle comprises the steps that firstly, a linear scale space is constructed by means of multi-scale Gaussian smoothing, then the local description length of an image is calculated and the optimum local smoothness scale is determined by means of the minimum description length principle, and finally edge detection is carried out on the image treated with local smoothing to obtain all edges of the weak edge image. The self-adaptive multi-scale image weak edge detection method based on the minimum description length principle has the advantages that common noise can be filtered effectively, a real weak edge can be extracted, and the phenomena of edge fracture, edge deviation, false edge responses and the like can be avoided; in addition, the algorithm used in the method is a non-iterative filter method, the computing speed is greatly improved, and the stability of the algorithm is greatly improved.

Description

technical field [0001] The present invention relates to an image weak edge detection method, in particular, it relates to an adaptive smoothing filtering method which utilizes local coherent diffusion and minimum description length criterion (minimum description length, MDL) to protect image weak edges and estimate local smoothing scale . Background technique [0002] The weak edge of the image is caused by the motion blur and defocus blur of the image, and the important spatial information contained in it has been widely used in the fields of machine vision, image restoration and image compression. In order to extract this kind of spatial information, these weak edges must be detected first, but the traditional edge detection methods are prone to misjudgment and missed detection of weak edges. The invention proposes a multi-scale image weak edge detection technology based on the minimum description length, which can improve the extraction efficiency of weak edges. [0003...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T5/00
Inventor 谭洪舟陈荣军徐秀峰熊文婷朱雄泳
Owner SUN YAT SEN UNIV
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