  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.
