A note on multi-image denoising

Toni Buades, Y. Lou, J. Morel, Zhongwei Tang
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引用次数: 98

Abstract

Taking photographs under low light conditions with a hand-held camera is problematic. A long exposure time can cause motion blur due to the camera shaking and a short exposure time gives a noisy image. We consider the new technical possibility offered by cameras that take image bursts. Each image of the burst is sharp but noisy. In this preliminary investigation, we explore a strategy to efficiently denoise multi-images or video. The proposed algorithm is a complex image processing chain involving accurate registration, video equalization, noise estimation and the use of state-of-the-art denoising methods. Yet, we show that this complex chain may become risk free thanks to a key feature: the noise model can be estimated accurately from the image burst. Preliminary tests will be presented. On the technical side, the method can already be used to estimate a non parametric camera noise model from any image burst.
关于多图像去噪的注意事项
在弱光条件下用手持相机拍照是有问题的。曝光时间过长会因相机抖动而产生运动模糊,曝光时间过短则会产生噪点图像。我们考虑了相机提供的新技术可能性,可以拍摄图像。每张图像都很清晰,但很嘈杂。在本初步研究中,我们探索了一种有效的多图像或视频去噪策略。该算法是一个复杂的图像处理链,涉及精确配准、视频均衡、噪声估计和使用最先进的去噪方法。然而,我们表明,由于一个关键特征:噪声模型可以从图像爆发中准确估计,这个复杂的链可能成为无风险的。将进行初步测试。在技术方面,该方法已经可以用于从任何图像突发估计非参数相机噪声模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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