Still image denoising based on discrete wavelet transform

Harnani Hassan, A. Saparon
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引用次数: 11

Abstract

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.
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基于离散小波变换的静止图像去噪
现代媒体传播行业的发展和对高质量视觉信息的需求,引起了研究者们对基于小波变换的图像去噪方法的兴趣。以图像形式传输的视觉信息自然会受到高斯噪声的破坏,这是图像处理中的经典问题。由于小波去噪技术能够在很少的能量变换值中捕获信号的能量,因此可以去除这种加性随机噪声。研究了基于正交小波基的图像去噪的小波阈值法和平移不变量法的适用性。图像去噪的性能从PSNR和视觉性能两方面来衡量。结果表明,平移不变量比小波变换具有更好的PSNR和视觉效果。
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