基于深度学习的图像去噪研究进展

A. Yapici, M. Akcayol
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引用次数: 1

摘要

卫星图像在图像捕获、传输或恶劣的环境条件下可能受到噪声的破坏。在日常生活和科学研究中,对更精确图像的需求越来越大。然而,图像被噪声扭曲,导致视觉图像质量降低。因此,对图像进行去噪研究以提高图像质量。到目前为止,人们提出了各种各样的方法来降低噪声,每种方法都有不同的优点。本文对视频和图像降噪领域的研究进行了总结,并进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Image Denoising With Deep Learning
Satellite images can be corrupted by noise during image capture, transfer or due to bad environmental conditions. In daily life and scientific searches, the need for more accurate images are increasing. However, images are distorted by noise, resulting in lower visual image quality. For this reason, noise removal studies are carried out on images to increase the quality. Until now, various methods have been proposed to decrease noise and each technique have different advantages. This paper, summarizes the studies in the field of noise reduction in video and images and compares the studies with each other.
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