Image Enhancement by Using Fuzzy Firefly Optimization and Fuzzy Perceptron Neural Network

Baydaa Khaleel
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引用次数: 0

Abstract

The image enhancement methods play an important role in digital image processing. And by using a different kinds of image enhancement techniques, such as artificial intelligence techniques methods. The aim of this methods is to enhance the visual appearance of the digital image and to reduce image noise. In this paper, to enhance the corrupted image and de-noise image, we used swarm optimization algorithms such as a firefly algorithm (FA) and also used neural network such as the perceptron neural network algorithm (PNN). And then after we added the fuzzy membership function to these two algorithms, we obtained to a new method called a fuzzy firefly algorithm (FFA) and fuzzy perceptron neural network algorithm (FPNN). And was computed the performance and efficiency measures for all methods, such as RMSE and PSNR. And the FFA method was the best among the other methods used in this paper.
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基于模糊萤火虫优化和模糊感知器神经网络的图像增强
图像增强方法在数字图像处理中起着重要的作用。并通过使用不同种类的图像增强技术,如人工智能技术方法。该方法的目的是增强数字图像的视觉外观并降低图像噪声。在本文中,我们使用了群体优化算法(如萤火虫算法(FA))和神经网络(如感知器神经网络算法(PNN))来增强损坏图像和去噪图像。然后在这两种算法中加入模糊隶属函数,得到一种新的算法,即模糊萤火虫算法(FFA)和模糊感知器神经网络算法(FPNN)。并计算了各方法的性能和效率指标,如RMSE和PSNR。其中,FFA法是本文所采用的几种方法中效果最好的。
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来源期刊
Periodica polytechnica Electrical engineering and computer science
Periodica polytechnica Electrical engineering and computer science Engineering-Electrical and Electronic Engineering
CiteScore
2.60
自引率
0.00%
发文量
36
期刊介绍: The main scope of the journal is to publish original research articles in the wide field of electrical engineering and informatics fitting into one of the following five Sections of the Journal: (i) Communication systems, networks and technology, (ii) Computer science and information theory, (iii) Control, signal processing and signal analysis, medical applications, (iv) Components, Microelectronics and Material Sciences, (v) Power engineering and mechatronics, (vi) Mobile Software, Internet of Things and Wearable Devices, (vii) Solid-state lighting and (viii) Vehicular Technology (land, airborne, and maritime mobile services; automotive, radar systems; antennas and radio wave propagation).
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