关键词: 自适应/
三高斯模型/
忆阻交叉阵列/
图像增强
English Abstract
An adaptive three-Gauss model based on memristive cross array and its application in image enhancement
Liu Qi,Wang Li-Dan,
Duan Shu-Kai
1.Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, School of Electronic and Information Engineering, Southweat University, Chongqing 400715, China
Fund Project:Project supported by the National Natural Science Foundation of China (Grant Nos. 61571372, 61672436, 61372139), the Fundamental Research Funds for the Central Universities, China (Grant Nos. XDJK2016A001, XDJK2014A009), and the Program for New Century Excellent Talents in University, China (Grant No. [2013]47).Received Date:11 January 2017
Accepted Date:31 March 2017
Published Online:05 June 2017
Abstract:In visual image processing, there is a three-Gauss model used to simulate the receptive field of retinal ganglion cells, which can realize image enhancement to a certain extent, such as image edge and information about details. However, in dealing with a large number of image data, it is necessary to manually adjust the parameters of the three-Gauss model in order to achieve better results, which is a very tedious and time-consuming process. According to this, in this paper we propose an adaptive three-Gauss model based on memristive cross array. Memristor, whose resistance is controlled by size, polarity and power supply time of the power supply, is a kind of non-volatile component. Moreover, if the voltage applied to both ends of memristor is removed, it can still keep the resistance value when the power is off. Many studies show that when voltage pulses with the different amplitudes and the same width are applied to both ends of the memristor, the resistance will change continuously. This principle is adopted to realize image storage. Therefore, it makes use of the characteristics of memristor in this paper. The proposed model is based on the traditional three-Gauss model and changes the model parameters by using the dynamic characteristics of memristive cross array according to the local characteristics of the image to be processed, in order to achieve the purpose of local optimization and make the whole image obtain better enhancement effect. First of all, according to the local brightness information of the image, the polarity and the width of the pulse voltage required by the memristor are determined. Then, the values of the model parameters corresponding to the memristance can be obtained. Finally, the local enhancement template will be available to realize the enhancement. In this paper, the color and gray images are selected. The qualitative and quantitative experimental results show that the proposed adaptive three-Gauss model based on memristive cross array can not only effectively enhance the edge contour of the image, but also greatly improve the image contrast and clarity. Moreover, it provides a new direction for the application of memristor to image processing.
Keywords: adaptive/
three-Gaussian model/
memristive crossbar array/
image enhancement
