Abstract
An extension of the fusion of interpolated frames superresolution (FIF SR) method to perform SR in the presence of atmospheric optical turbulence is presented. The goal of such processing is to improve the performance of imaging systems impacted by turbulence. We provide an optical transfer function analysis that illustrates regimes where significant degradation from both aliasing and turbulence may be present in imaging systems. This analysis demonstrates the potential need for simultaneous SR and turbulence mitigation (TM). While the FIF SR method was not originally proposed to address this joint restoration problem, we believe it is well suited for this task. We propose a variation of the FIF SR method that has a fusion parameter that allows it to transition from traditional diffraction-limited SR to pure TM with no SR as well as a continuum in between. This fusion parameter balances subpixel resolution, needed for SR, with the amount of temporal averaging, needed for TM and noise reduction. In addition, we develop a model of the interpolation blurring that results from the fusion process, as a function of this tuning parameter. The blurring model is then incorporated into the overall degradation model that is addressed in the restoration step of the FIF SR method. This innovation benefits the FIF SR method in all applications. We present a number of experimental results to demonstrate the efficacy of the FIF SR method in different levels of turbulence. Simulated imagery with known ground truth is used for a detailed quantitative analysis. Three real infrared image sequences are also used. Two of these include bar targets that allow for a quantitative resolution enhancement assessment.
Highlights
Designing imaging systems involves a complex trade space
We present the overall optical transfer function (OTF) model used for the fusion of interpolated frames superresolution (FIF SR) restoration
We present a number of experimental results to demonstrate the efficacy of the fusion of interpolated frames (FIF) SR method with both
Summary
Designing imaging systems involves a complex trade space. The focal plane array detector pitch determines the spatial sampling frequency, and the f-number of the optics and wavelength determine the diffraction-limited optical cutoff frequency. It incorporates the level of registration that impacts the residual atmospheric blurring and the level of subpixel weighting that impacts the interpolation blur We believe this smart OTF model allows the Wiener filter to better restore the fused image and provide improved performance. One interesting result we show is that the tilt variance from turbulence can improve SR results, compared with no turbulence, when no camera platform motion is present In this case, the random wavefront tilts provide the critical relative motion between the scene and camera for SR sampling diversity, as described by Fishbain et al.[10] and Yaroslavsky et al.[11] We believe our simulation study is the first quantitative error analysis of its kind to demonstrate this phenomenon in the literature.
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