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Image edge detection method based on six-order spline scale function

A scaling function and image edge technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as wavelet transform is difficult

Active Publication Date: 2020-01-03
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In dynamic target recognition, it is difficult for classical wavelet transform to adjust the resolution of wavelet transform and signal processing area in real time according to image changes.

Method used

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  • Image edge detection method based on six-order spline scale function
  • Image edge detection method based on six-order spline scale function
  • Image edge detection method based on six-order spline scale function

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Embodiment Construction

[0054] 1. An image edge detection method based on the sixth-order spline scaling function, the steps are as follows:

[0055] (1) The set image can be expressed as a matrix M, such as figure 1 As shown, the matrix consists of 500×400 pixels,

[0056] (2) Selected function, where w is the angular frequency

[0057]

[0058] (3) Selected function

[0059]

[0060] (4) Based on formula (2), calculate the function

[0061]

[0062] (5) Calculated based on formulas (2) and (3), where i is the imaginary unit

[0063] Q ψ (w)=-e -iw / 2 E. φ (w+2π)P φ (w+2π) (4)

[0064] (6) Based on (1), (4) formula

[0065]

[0066] (7) Based on formula (5), inverse Fourier transform is performed to obtain ψ(x),

[0067] (8) Based on formula (1), do Fourier inverse transform to get φ(x),

[0068] (9) Selected matrix

[0069]

[0070] In the formula,

[0071] lambda -10 =-0.0003λ -9 =0.0006λ -8 =-0.0012λ -7 =0.0023λ -6 =-0.0041

[0072] lambda -5 =0.0074λ -4 =-0.0128λ...

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Abstract

The invention relates to an image edge detection method based on a six-order spline scale function, and solves the problem that the resolution of wavelet transform and a signal processing area are difficult to adjust in real time according to image change in traditional wavelet transform. According to the invention, the wavelet edge extraction capability and the adaptive capability of the neural network are combined; firstly, matrixes Psi 1, Psi 2, Phi1 and Phi2 are obtained through a six-order spline scale function and a six-order spline wavelet function, then the matrixes Psi 1, Psi 2, Phi1and Phi2 are obtained, matrixes Q1 and Q2 are used for obtaining the matrixes, then the matrixes are obtained based on an image matrix M, and finally an image edge B is obtained through use. And dynamic adjustment of the wavelet transform resolution and the signal processing area is realized in the image edge extraction process, so that finer and more accurate edges can be obtained.

Description

technical field [0001] The invention is related to the fields of image processing, computer vision, pattern processing and the like. Background technique [0002] Image edge detection is a fundamental problem in image processing and computer vision. The purpose of image edge detection is to identify points in a digital image where there are significant changes in brightness. Image edge detection can filter out information that can be considered irrelevant, retain important feature information of the image, and greatly reduce the amount of data, thereby reducing the time and space overhead of computer processing. Neural network is an algorithmic mathematical model that imitates the behavior characteristics of animal neural networks and performs distributed parallel information processing. This kind of network depends on the complexity of the system, and achieves the purpose of processing information by adjusting the interconnection relationship between a large number of int...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/13G06T7/168
CPCG06T7/13G06T7/168G06T2207/20064G06T2207/20084
Inventor 张治国崔琼
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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