基于恒模平均和ANFIS的盲图像复原

Sui Li-yun, Ma Hong, Li Zheng, Ju Sheng-gen
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引用次数: 7

摘要

本文提出了一种新的模糊噪声图像复原方法。假设模糊的噪声图像是一个被加性噪声污染的未知点扩展函数的线性空间不变系统的输出。该方案将模糊的噪声图像通过二维有限脉冲响应滤波器,该滤波器的参数由带平均和自适应神经模糊推理系统的改进常模算法更新。当收敛发生时,滤波器的输出是对未观察到的真实图像的估计。实验结果表明,该方案是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind Image Restoration Based on Constant Modulus with Averaging and ANFIS
In this paper, a new approach for blurred noisy image restoration is presented. The blurred noisy image is assumed to be the output of a linear space-invariant system with an unknown point spread function contaminated by an additive noise. The scheme passes the blurred noisy image through a two-dimensional finite impulse response filter whose parameters are updated by the modified constant modulus algorithm with averaging and adaptive neuro- fuzzy inference system. When convergence occurs, the output of the filter is an estimate of the unobserved true image. Experimental results show that the proposed scheme is effective.
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