基于线性约束最小二乘法的噪声图像融合神经动力学方法

2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM) Pub Date : 2019-01-01 DOI:10.1109/AIAIM.2019.8632778

Jihui Yu, Chuandong Li

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引用次数: 0

摘要

本文提出了一种神经动力学方法，通过融合噪声图像来去除高斯噪声。提出了一种基于线性约束最小二乘(LCLS)方法的RGB通道图像融合约束优化问题。此外，还引入了神经动力学模型，分别求解了三个通道的优化问题。实验结果证实了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Neurodynamic Approach to Noisy Image Fusion Based on a Linear Constrained Least Square Method

In this paper, a neurodynamic approach is proposed to denoise Gaussian noise through fusing noisy images. A constrained optimization problem based on a linearly constrained least square (LCLS) method is introduced for image fusion in RGB channels. Moreover, a neurodynamic model is introduced to solve the optimization problem in three channels respectively. Experimental results substantiate the efficacy of the proposed approach.

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来源期刊

2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM)

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