A New Kind of Image Edge Detection Based on The Theory of The Adaptive Lifting Wavelet and Morphology

2018 ◽  
Vol 11 (3) ◽  
pp. 90-104
Author(s):  
Honge Ren ◽  
Xiyan Xu ◽  
Meng Zhu ◽  
Dongxu Huo

This article describes how in traditional edge detection it is prone to defects such as fuzzy positioning, and noise influence. This article proposes a type of edge detection algorithm which combines lifting wavelet transform and adaptive mathematical morphology, which makes a lifting wavelet to analyze the wood cell image. Then, the high-frequency part is detected by using the algorithm fusing the wavelet packet and the rapid-combining multi-scale wavelet, which controls noise effectively; while for the low frequency part is detected with modified adaptive mathematical morphology, to locate the exact details. The final result will processes the edge of the image using “algebra” algorithm fusion. The example for a wood cell image which illustrates the algorithm is to detect the cell boundary relatively clearly, and effectively suppress the noise.

2013 ◽  
Vol 467 ◽  
pp. 599-603 ◽  
Author(s):  
Hui De Li ◽  
Lian Yu Zhao

The image edge detection algorithm is one of the most important steps in the image processing, however, while the large amount of data is need to be dealt with in the detection process, it is difficult to meet real-time requirements by using the software method. In order to improve the speed of digital image processing, An embedded processing systems based on FPGA (field-programmable gate array) detection algorithm is proposed, which takes corrosion expansion algorithm of mathematical morphology as its theoretical basis to achieve the task of image edge detection, experiments result show the method is effective and feasible, and meets the real-time requirement of the image processing.


2013 ◽  
Vol 441 ◽  
pp. 670-673
Author(s):  
Zhong Hai Zhou ◽  
Jian Yuan ◽  
Jun Xiao Li

An interference image edge detection method for laser interferometer hydrophone based on wavelet packet is investigated. Considering the effect of ocean background noise on the interference image, we propose the use of a class of wavelet packet functions to make decomposition on noisy interference image, and then make reconstruction on approximate parts of the decomposed image. The approximate parts with the wavelet packet decomposition is of more clear image layers comparison to the original image, and the wavelet packet decomposition method can reduce the influence of background noise on the interference image. Taking the wavelet packet decomposition method and other edge detection algorithms for contrast, it is proved that the wavelet packet decomposition method for edge detection algorithm is more effective than the other algorithms.


2012 ◽  
Vol 591-593 ◽  
pp. 1822-1826
Author(s):  
Kun Xian He ◽  
Qing Wang ◽  
Fan He

This paper presents a fusion algorithm for image edge detection based on the mathematical morphology and the NSCT. First the de-noised image is processed by the multi-structure elements of the mathematical morphology. And then the processed image is decomposed by the NSCT into multi-scale and multi-directional sub-bands. Edges in the high-frequency sub-bands are extracted with the dual-threshold modulus maxima method. Finally the edges of the de-noised image are refined into a single pixel edge image. The simulation results show that this method can effectively suppress noise, eliminate pseudo-edges, locate accurately and detect the complete outline.


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