基于序列图像的改进NLM去噪方法

Proceedings of the 6th International Conference on Information and Education Technology Pub Date : 2018-01-06 DOI:10.1145/3178158.3178192

L. Yihan, Wang Yun, Yang Wei

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引用次数: 1

摘要

提出了一种改进的基于多幅图像的非局部均值去噪方法。该方法的主要思想是利用多幅序列图像来提高NLM算法的去噪性能。该方法既考虑了图像的自相似性，又利用了序列图像之间的相似性。用不同噪声水平的合成图像和真实图像对该算法进行了验证。引入了PSNR和SSIM来评价处理后的图像质量。实验表明，该算法能够在去除噪声的同时保留图像的细节。

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A modified NLM method for noise remove based on sequential images

This paper proposes an improved Non-Local Means denoising method based on multiple images. The main idea of this method is to use several sequential images to improve the denoising performance of NLM algorithm. This method not only takes into consideration the self-similarity of images, but also uses the similarity between sequential images. This algorithm has been verified by using synthetic images with different levels of noise and real images. PSNR and SSIM has been introduced to evaluate the quality of images after processing. Experiments show that this algorithm is able to remove the noise, and retain the details of images at the same time.

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Proceedings of the 6th International Conference on Information and Education Technology

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