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AN IMPROVED NAS-RIF ALGORITHM BASED ON THE WAVELET DENOISING AND IMAGE SEGMENTATION

机译:一种改进的基于小波去噪和图像分割的RIF算法

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An improved method is presented in this paper to overcome drawbacks of the original NAS-RIF algorithm. To begin with, the wavelet denoising technique is used to preserve the edge feature of the degraded image, restrain noise amplification, and increase the Signal-to-Noise Ratio (SNR); then, the image segmentation technique is applied in each iteration to find the precise support region of the object, where the non-uniform background is replaced by the mean of the background; the algorithm resetting of the convergence of the conjugate gradient is also employed here to speed up the convergence rate. The improved algorithm is experimentally shown to have better restoration effect and faster convergence rate.
机译:本文提出了一种改进的方法,以克服原始NAS-RIF算法的缺点。首先,小波去噪技术用于保留降级图像的边缘特征,抑制噪声放大,增加信噪比(SNR);然后,在每次迭代中应用图像分割技术以找到对象的精确支撑区域,其中非均匀背景被背景的均值取代;这里使用缀合物梯度的收敛算法的算法重置,以加速收敛速率。改进的算法实验显示具有更好的恢复效果和更快的收敛速度。

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