Equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method

Abstract

The invention discloses an equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method. The equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method comprises the following steps of performing three-layer wavelet decomposition on an image through an equal-even length anti-symmetrical biorthogonal wavelet by a Mallat algorithm; calculating a gradient vector modulus value graph and a phase angle graph according to every scale of wavelet decomposition data of the image; detecting a modulus maxima point of every scale according to the direction determined by the phase angle graph; removing pseudo boundary points by a threshold value method; integrating obtained scales of boundary point sets so as to obtain the accurate single pixel width of boundary. According to the equal-even length anti-symmetrical biorthogonal wavelet filter group based edge detection method, the wavelet decomposition is performed through an equal-even length anti-symmetrical biorthogonal wavelet filter group with the differential operator function, the boundary information of every scale is comprehensively utilized, and accordingly the integrity and the accuracy of edge detection of the image are improved and certain anti-noise performance is achieved.

Description

technical field [0001] The invention relates to an edge detection method based on an equal-even-length antisymmetric biorthogonal wavelet filter bank. Background technique [0002] The edge in the image is the most important feature for segmentation and recognition of the content in the image, so edge detection has always been one of the research focuses of image processing and computer vision. Traditional edge detection methods, such as Roberts operator, Sobel operator, Prewitt operator, Laplace operator, etc., are only suitable for edge detection at a single scale, and when the target is weak to a certain extent and the background noise is serious , edge extraction cannot be achieved. Wavelet transform is widely used in the field of signal and image processing with its excellent time-frequency domain localization and multi-resolution analysis capabilities, such as signal denoising, image compression, multi-scale edge detection and image segmentation, but it is used for ed...

AI Technical Summary

Problems solved by technology

However, when the general antisymmetric biorthogonal wavelet filter bank is used for edge detection, the integrity is not high and the anti-noise performance is poor.

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