论文标题
UG2+挑战2022的第二名解决方案-D $^{3} $ net用于减轻图像的大气湍流
2nd Place Solutions for UG2+ Challenge 2022 -- D$^{3}$Net for Mitigating Atmospheric Turbulence from Images
论文作者
论文摘要
该技术报告简要介绍了我们的团队“ tuk-iklab”提出的D $^{3} $网络，以减轻$ ug2^{+} $挑战的大气湍流2022。根据测试和验证结果，鉴于对文本识别性能和图像的验证，可以提出建议的效果，以提高建议，以提高您的建议，以提高您的建议。此外，我们还提供了与拟议工作的公开可用的DeNoising，Deblurring和框架平均方法的视觉比较。所提出的方法分别在测试阶段的上述挑战的最终领导板上排名第二。
This technical report briefly introduces to the D$^{3}$Net proposed by our team "TUK-IKLAB" for Atmospheric Turbulence Mitigation in $UG2^{+}$ Challenge at CVPR 2022. In the light of test and validation results on textual images to improve text recognition performance and hot-air balloon images for image enhancement, we can say that the proposed method achieves state-of-the-art performance. Furthermore, we also provide a visual comparison with publicly available denoising, deblurring, and frame averaging methods with respect to the proposed work. The proposed method ranked 2nd on the final leader-board of the aforementioned challenge in the testing phase, respectively.
