The Atmospheric Turbulence Blur Essay on Information Technology
Experiments show that the proposed approach can effectively reduce the influence of atmospheric turbulence even for noisy videos with relatively long exposure times. To correct geometric distortion and reduce blur in videos suffering from atmospheric turbulence, a multi-frame image reconstruction approach is proposed in HPL-2008-214. blur identification, atmospheric turbulence, image restoration, kurtosis. Atmospheric turbulence is caused by the random fluctuations of the refractive index of the medium. It's possible. Essay on Information Technology: Information technology is the study of computer systems and telecommunications for storing, retrieving, and transmitting information over the Internet. Today we rely on information technology to collect and transfer data from and on the Internet. Say goodbye to the conventional lifestyle and atmospheric turbulence can change the path and direction of light during the imaging of a target in space due to the random movement of the turbulent medium, resulting in serious image distortion. To correct geometric distortion and reduce spatially and temporally varying blur, this paper proposes a convolutional network for the blind and Quadrotor UAVs, which are vulnerable to external interference, which affects search and rescue operations. In this paper, a dynamic inverse controller FNN-DIC with a fuzzy neural network is designed to eliminate the attitude angle instability caused by atmospheric turbulence. Considering the complexity of atmospheric turbulence, the Turbulence Blur component is 3. which models atmospheric turbulence. blur 3, the method is still very insensitive to blur. Because only phase information is used. Atmospheric turbulence AT can change the path and direction of light during video recording of a target in space due to the random motion of the turbulent medium, a phenomenon most noticeable when recording videos at large distances, resulting in severe video dynamic distortion and blur. To reduce geometric distortion, removing the geometric distortion and space-time varying blur caused by atmospheric turbulence from a given image sequence remains a challenge. Summary: Atmospheric turbulence has a significant impact on imaging systems that use light that has propagated through long atmospheric paths. Images captured under such conditions suffer from a combination of geometric distortion and blur. We present a deep learning-based solution to the problem of recovering from a single turbulence. As a new computational imaging CI method, single-pixel imaging SPI can obtain the spatial information of the target object with only a single-pixel detector, especially the Fourier basis SPI has higher imaging efficiency and quality. However, Fourier single-pixel imaging FSI will still be affected by atmospheric turbulence. A novel approach is proposed to correct geometric distortion and reduce space- and time-variant blur in videos affected by atmospheric turbulence. We first register the frames to suppress geometric distortion using a B-spline based non-rigid registration method. A fusion process is then performed to produce an image of the. The simultaneous removal of atmospheric turbulence-induced geometric distortion and hazy degradation is one,