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Image denoising using wavelet transform and median filtering

机译:使用小波变换和中值滤波的图像去噪

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During acquisition of an image, from its source, noise becomes integral part of it, which is very difficult to remove. Various algorithms have been used in past to denoise images. Image denoising still has scope for improvement. In this paper we present a new image denoising algorithm based on combined effect of wavelet transform and median filtering. The algorithm removes most of the noisy part from the image and maintains the quality. The level of wavelet decomposition is restricted to three. The renowned index Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) demonstrate marked improvement of image denoising over other methods.
机译:在获取图像期间,从其源极,噪声变成它的组成部分,这很难移除。过去已经使用了各种算法以去代标图像。图像去噪仍然具有改进的范围。本文介绍了一种基于小波变换和中值滤波的组合效应的新图像去噪算法。该算法从图像中删除大多数嘈杂部件并保持质量。小波分解的水平仅限于三个。噪声比(PSNR)和根均方误差(RMSE)的着名指数峰值信号证明了图像去噪的显着改善。

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