A novel approach for mitigating atmospheric turbulence using weighted average Sobolev gradient and Laplacian. (11th September 2019)

• Record Type: Journal Article
• Authors: Nunes, Prifiyia; Israni, Dippal; D., Karthick; Shah, Arpita
• Is Part Of: International journal of computational vision and robotics. Volume 9:Number 5(2019)
• Page Start: 515
• Page End: 526
• Publication Date: 2019-09-11
• Subjects: atmospheric turbulence -- heat scintillation -- restoration -- Sobolev -- phase shift -- weighted average; Computer vision -- Periodicals; Robotics -- Periodicals; Artificial intelligence -- Periodicals; 006.3705
• Languages: English
• ISSNs: 1752-9131

Abstract

Heat scintillation mainly leads to atmospheric turbulence which causes the image distortion due to the propagation of light through the volatile environment. The change in the refractive index due to variation in wind velocity is also the reason for causing turbulence in the atmosphere. Traditional image registration approach lags as it is computationally expensive and need post-processing algorithm for sharpening the image. A non-registration-based Sobolev gradient and Laplacian (SGL) algorithm removes turbulence but results in ghost artifacts in moving objects. This paper proposes a novel approach based on weighted average SGL. The proposed method mitigates atmospheric turbulence as well as restores the moving object in the scene. Performance metrics like SSIM and MSE prove that the proposed algorithm outperforms the state of the art algorithms in terms of restoring the geometric distortion as well as the object of interest.