概述:使用生成对抗网络进行图像增强的超图像分辨率

Ravindra Singh Kushwaha, Manik Rakhra, Dalwinder Singh, Ashutosh Kumar Singh
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引用次数: 1

摘要

图像处理在数据分析过程中起着至关重要的作用,无论何时从设备上获取图像,都不可能发现图像质量差或发现大量噪声。本文研究的是SRGAN的子部分,它有助于对图像进行处理以获得图像的HR。通过使用SRGAN,我们只需要输入图像的低分辨率,经过数据处理后就会转换成高分辨率图像。在这里,我们回顾了所有相关的SRGAN论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Overview: Super-Image Resolution using Generative Adversarial Network for Image Enhancement
Image processing plays a vital role during the analysis of the data, whenever the image is taken from the device it is not possible that the quality of the image is poor or found a lot of noise. This paper is working on the GAN’s subpart of SRGAN, which helps in processing of the image to get the HR of the image. By using the SRGAN, we just need to input the image’s low resolution, and after processing the data it will convert into a high-resolution image. Here we are reviewing all the related SRGAN papers.
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