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Performance Analysis of Various Spatial Filters on Noisy Images - A Quantitative Approach

机译:噪声图像上各种空间滤波器的性能分析-一种定量方法

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Choosing a suitable denoising filter acts a significant role in the image restoration procedure. Smoothing or reduction of noise present in the image is a significant preprocessing task before segmenting and analyzing the features present in an image. This paper is focused on choosing a desired filter for performing denoising process through some of the well-known image quantitative metrics. Some of the traditional filters are taken for experimentation and quantitative results are compared. In order to evaluate the degree of smoothness of the resultant images, quantitative metrics such as MSSIM (Mean Structural Similarity Index), PSNR (Peak Signal-to-Noise Ratio), and MSE (Mean Square Error) are used. This paper gives guidance in selecting an appropriate filter for performing denoising process through quantitative metrics.
机译:选择合适的降噪滤波器在图像恢复过程中起着重要作用。在分割和分析图像中存在的特征之前,平滑或减少图像中存在的噪声是一项重要的预处理任务。本文的重点是通过一些众所周知的图像定量指标来选择用于执行降噪处理的所需滤波器。采用了一些传统的过滤器进行实验,并对定量结果进行了比较。为了评估所得图像的平滑度,使用了诸如MSSIM(均值结构相似性指数),PSNR(峰值信噪比)和MSE(均方误差)之类的定量指标。本文为通过量化指标选择合适的滤波器进行去噪处理提供了指导。

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