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Still image denoising based on discrete wavelet transform

机译:基于离散小波变换的静止图像去噪

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The growth of media communication industry and demand of high quality of visual information in modern age has open an interest to researcher to develop varies method of image denoising based on DWT. The visual information transmitted in form of image is naturally corrupted by Gaussian noise which is classical problem in image processing. This additive random noise can be removed using wavelet denoising technique due to the ability to capture the energy of a signal in few energy transform values. In this paper, an investigation has been made on suitability wavelet thresholding and translation invariant methods of image denoising to remove noise using orthogonal wavelet basis. The performance of the image denoising is shown in terms of PSNR and visual performance. The result shown translation invariant gave better PSNR and visual performance than wavelet transform method.
机译:现代时代的媒体通信行业的增长和高质量的视觉信息的需求对研究人员开辟了兴趣,该兴趣开发基于DWT的图像去噪模式。以图像形式发送的视觉信息由高斯噪声自然破坏,这是图像处理中的经典问题。由于能够在少量能量变换值中捕获信号的能量,可以使用小波去噪技术去除这种添加剂随机噪声。在本文中,对使用正交小波除去噪声的图像去除的适用性小波阈值和翻译不变方法进行了研究。在PSNR和视觉性能方面显示了图像去噪的性能。结果显示的转换不变导致比小波变换方法更好的PSNR和视觉性能。

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