An intelligent method of extracting an infrared image edge based on lateral inhibition

2006 ◽  
Author(s):  
Kang-lin Gao ◽  
Mei Dong ◽  
Feng-qi Zhou
Keyword(s):  
Lateral Inhibition ◽  
Infrared Image ◽  
Image Edge ◽  
Edge Based

A Lifting Wavelet Structure Based on Lateral Inhibition Characteristics

2013 ◽  
Vol 631-632 ◽  
pp. 1287-1292
Author(s):  
Hong Ye Xue ◽  
Yan Zhang
Keyword(s):  
Lateral Inhibition ◽  
Infrared Image ◽  
Lifting Scheme ◽  
Redundant Information ◽  
Construction Process ◽  
Real Time Processing ◽  
Time Processing ◽  
Image Edge ◽  
The Difference ◽  
Wavelet Lifting

Aiming at the question of infrared image edge to enhance and the real-time processing, this paper researches a Bubble wavelet construction process which can remove redundant information, strengthen the difference of information and have the lateral inhibition characteristics ,derives the Bubble wavelet lifting scheme and the lifting coefficient , and finally with the application of the lifting scheme, we realize the parallel computing aiming at the infrared image decomposition and reconstruction, the results show that based on lateral inhibition characteristics of the Bubble wavelet lifting scheme is correct, and also proves the usability of the lifting coefficient.

The Implementation of Infrared Image Edge Detection Algorithm Based on CNN on FPGA

2012 ◽  
Vol 41 (11) ◽  
pp. 1354-1358 ◽  
Author(s):  
王巍 WANG Wei ◽  
安友伟 AN You-wei ◽  
黄展 HUANG Zhan ◽  
丁锋 DING Feng ◽  
杨铿 YANG Keng ◽  
...  
Keyword(s):  
Edge Detection ◽  
Infrared Image ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Image Edge

Infrared image edge recognition and defect quantitative determination based on the algorithm of fuzzy C-means clustering and Canny operator

2016 ◽  
Vol 45 (9) ◽  
pp. 928001
Author(s):  
唐庆菊 Tang Qingju ◽  
刘俊岩 Liu Junyan ◽  
王 扬 Wang Yang ◽  
刘元林 Liu Yuanlin ◽  
梅 晨 Mei Chen
Keyword(s):  
Quantitative Determination ◽  
Infrared Image ◽  
Canny Operator ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Image Edge ◽  
Edge Recognition

A New Infrared Image Magnification and Enhancement Method Based on Wavelet Transform

2012 ◽  
Vol 198-199 ◽  
pp. 238-243 ◽  
Author(s):  
Wen Sheng Guo ◽  
Feng Chen ◽  
Zhao You Sun ◽  
Xi Jun Wang
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Infrared Image ◽  
Low Frequency ◽  
High Energy ◽  
Low Energy ◽  
Image Magnification ◽  
Edge Profile ◽  
Enhancement Method ◽  
Image Edge

The traditional image magnify method usually have some defects on details. This paper gives a new infrared image magnification and enhancement method which is based on wavelet reconstruction and gradation segment. In this method, first of all, make wavelet transform on the image, get the high-frequency coefficient. Apply the Newton differential algorithm enhance the high-frequency coefficient as the high-frequency part of the magnified image, treat the original image as the low-frequency part , make the wavelet reconstruction ,then get the magnified image. To enhance the magnified image, according to the double gray threshold, segment the image into high gray segment corresponding to target, low gray segment corresponding to background, and middle gray segment corresponding to transition sector. Then, make linear extension to them respectively; the result is the magnified image. Experiments indicate, this method is effective on distinguishing high-energy target from low-energy target (the low-energy target is the primary one) and displaying the details of image(edge profile of the bomb).

scholarly journals Stochastic Fractal Search Algorithm for Template Matching with Lateral Inhibition

2017 ◽  
Vol 2017 ◽  
pp. 1-14
Author(s):  
Qifang Luo ◽  
Sen Zhang ◽  
Yongquan Zhou
Keyword(s):  
Lateral Inhibition ◽  
Template Matching ◽  
Search Algorithm ◽  
Inhibition Mechanism ◽  
Edge Extraction ◽  
Matching Problems ◽  
Matching Technique ◽  
Image Edge ◽  
Stochastic Fractal Search Algorithm ◽  
Stochastic Fractal Search

Template matching is a basic and crucial process for image processing. In this paper, a hybrid method of stochastic fractal search (SFS) and lateral inhibition (LI) is proposed to solve complicated template matching problems. The proposed template matching technique is called LI-SFS. SFS is a new metaheuristic algorithm inspired by random fractals. Furthermore, lateral inhibition mechanism has been verified to have good effects on image edge extraction and image enhancement. In this work, lateral inhibition is employed for image preprocessing. LI-SFS takes both the advantages of SFS and lateral inhibition which leads to better performance. Our simulation results show that LI-SFS is more effective and robust for this template matching mission than other algorithms based on LI.

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