Stabilizing and deblurring atmospheric turbulence

A new approach is proposed to correct geometric distortion and reduce space and time-variant blur in videos that suffer from atmospheric turbulence. We first register the frames to suppress geometric deformation using a B-spline based non-rigid registration method. Next, a fusion process is carried out to produce an image from the registered frames, which can be viewed as being convolved with a space invariant near-diffraction-limited blur. Finally, a blind deconvolution algorithm is implemented to deblur the fused image. Experiments using real data illustrate that this approach is capable of alleviating blur and geometric deformation caused by turbulence, recovering details of the scene and significantly improving visual quality.

[1]  F. Hampel.  The Influence Curve and Its Role in Robust Estimation , 1974 .

[2]  M A Vorontsov,et al.  Anisoplanatic imaging through turbulent media: image recovery by local information fusion from a set of short-exposure images. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[3]  W. Middleton,et al.  Vision Through the Atmosphere , 1952 .

[4]  Michael F. Cohen,et al.  Seeing Mt. Rainier: Lucky imaging for multi-image denoising, sharpening, and haze removal , 2010, 2010 IEEE International Conference on Computational Photography (ICCP).

[5]  Richard Szeliski,et al.  PSF estimation using sharp edge prediction , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[6]  M. Vorontsov,et al.  The principles of adaptive optics , 1985 .

[7]  B. Welsh,et al.  Imaging Through Turbulence , 1996 .

[8]  Brent Ellerbroek,et al.  Advances in Adaptive Optics II , 2006 .

[9]  Marius Tico,et al.  Image enhancement method via blur and noisy image fusion , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[10]  Jiaya Jia,et al.  High-quality motion deblurring from a single image , 2008, ACM Trans. Graph..

[11]  Mikhail A. Vorontsov.  Parallel image processing based on an evolution equation with anisotropic gain: integrated optoelectronic architectures , 1999 .

[12]  Steven J. Simske,et al.  Atmospheric Turbulence-Degraded Image Restoration Using Principal Components Analysis , 2007, IEEE Geoscience and Remote Sensing Letters.

[13]  Michael C. Roggemann,et al.  Image-spectrum signal-to-noise-ratio improvements by statistical frame selection for adaptive-optics imaging through atmospheric turbulence , 1994 .

[14]  D. Fried.  Probability of getting a lucky short-exposure image through turbulence* , 1978 .

[15]  Masatoshi Okutomi,et al.  Super-resolution from image sequence under influence of hot-air optical turbulence , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Mikhail A. Vorontsov,et al.  Automated video enhancement from a stream of atmospherically-distorted images: the lucky-region fusion approach , 2009, Optical Engineering + Applications.

[17]  Robert N. Tubbs,et al.  Lucky Exposures:: Diffraction Limited Astronomical Imaging through the Atmosphere , 2003 .

[18]  Nicholas M. Law,et al.  Lucky imaging: diffraction-limited astronomy from the ground in the visible , 2007 .

[19]  Cambridge,et al.  Lucky imaging: High angular resolution imaging in the visible from the ground , 2005, astro-ph/0507299.

[20]  Mikhail A. Vorontsov,et al.  Image enhancement by local information fusion with pre-processing and composed metric , 2008, Optical Engineering + Applications.

[21]  Xiang Zhu,et al.  Image reconstruction from videos distorted by atmospheric turbulence , 2010, Electronic Imaging.

[22]  K. Knox.  Image retrieval from astronomical speckle patterns , 1976 .

[23]  Michael Elad,et al.  A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur , 2001, IEEE Trans. Image Process..

[24]  William T. Freeman,et al.  Removing camera shake from a single photograph , 2006, SIGGRAPH 2006.

[25]  S. John,et al.  Multiframe selective information fusion from robust error estimation theory , 2005, IEEE Transactions on Image Processing.

[26]  Russell B. Makidon,et al.  Strehl ratio and image sharpness for adaptive optics , 2006, SPIE Astronomical Telescopes + Instrumentation.