Blind image quality metrics for optimal speckle image reconstruction in horizontal imaging scenarios

Bos, Jeremy P.; Roggemann, Michael C.

doi:10.1117/1.oe.51.10.107003

Cited by 10 publications

(5 citation statements)

References 20 publications

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“…A median filter, a nonlinear operation, is more effective than convolution in order to reduce noise and preserve edges simultaneously (Brownrigg, 1984;Lin and Willson Jr, 1988;Sun and Neuvo, 1994;Wang and Zhang, 1999;Arias-Castro and Donoho, 2009). A 3 × 3 median filter is applied to the raw image (R) to obtain the processed image (P ):…”

Section: Step 1 -Filtering the Raw Image With A Median Filtermentioning

confidence: 99%

“…The sharpness of an image measured after high pass filtering was used for real-time frame selection by the Swedish Vacuum Solar Telescope (Scharmer, 1989). Bos and Roggemann (2012) compared the effect of sharpness and entropy in tuning the inverse filter used for amplitude recovery in a speckle imaging system. The Fisher information is a measure of disorder and was used by Zhang, Suess, and Mackay (2006) for searching lucky images.…”

Section: Introductionmentioning

confidence: 99%

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Objective Image-Quality Assessment for High-Resolution Photospheric Images by Median Filter-Gradient Similarity

et al. 2015

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All next generation ground-based and space-based solar telescopes require a good quality assessment metric in order to evaluate their imaging performance. In this paper, a new image quality metric, the median filter gradient similarity (MFGS) is proposed for photospheric images. MFGS is a noreference/blind objective image quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that: (1)the measured value of MFGS changes monotonically from 1 to 0 with degradation of image quality; (2)there exists a linear correlation between the measured values of MFGS and root-mean-squarecontrast (RMS-contrast) of granulation; (3)MFGS is less affected by the image contents than the granular RMS-contrast. Overall, MFGS is a good alternative for the quality assessment of photospheric images.

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Section: Step 1 -Filtering the Raw Image With A Median Filtermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Objective Image-Quality Assessment for High-Resolution Photospheric Images by Median Filter-Gradient Similarity

et al. 2015

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“…This new image quality metric is compared to three other image quality metrics: Muller and Buffington's S2 metric (Sharpness) [7], Sobel Edge Moment (SEM) Variance [8], and Laplacian of Gaussian (LoG) [9]. Sharpness is the sum of squares of the pixel values of the image (where the image is denoted as ) divided by the squared sum of the image's pixel values.…”

Section: Other Metricsmentioning

confidence: 99%

A new performance metric for hybrid adaptive optics systems

Werth

Bos

Calef

et al. 2014

2014 IEEE Aerospace Conference

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Advances in Adaptive Optics (AO) systems and image processing techniques have allowed image reconstruction to reach new levels of sophistication with impressive improvements in resolvability. The products of these reconstruction methods are often compared by eye due to a lack of widely agreed-upon objective performance metrics. This paper describes a new technique for assessing the performance of image reconstruction algorithms and AO systems. A line spread function is extracted from an object's edges, and the full width at half maximum of this experimentally measured line spread function is compared to the full width at half maximum of the system's diffraction-limited line spread function. This technique is used with imagery of satellites taken with the 3.6m Maui AEOS telescope with and without an AO system and with image post-processing. The AO system in question allows for rapid switching between compensated and uncompensated imagery, so an objective comparison between the two is possible.

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“…One important class of turbulence mitigation algorithms is bispectral speckle imaging. [6][7][8][9][10][11][12][13][14][15][16] This method seeks to recover the ideal image in the Fourier domain, by estimating the magnitude and phase spectrum separately. The magnitude spectrum is obtained with an inverse filter, or pseudoinverse filter, based on the LE optical transfer function (OTF).…”

Section: Introductionmentioning

confidence: 99%

Block matching and Wiener filtering approach to optical turbulence mitigation and its application to simulated and real imagery with quantitative error analysis

Hardie

Rucci

Dapore³

et al. 2017

Opt. Eng.

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We present a block-matching and Wiener filtering approach to atmospheric turbulence mitigation for long-range imaging of extended scenes. We evaluate the proposed method, along with some benchmark methods, using simulated and real-image sequences. The simulated data are generated with a simulation tool developed by one of the authors. These data provide objective truth and allow for quantitative error analysis. The proposed turbulence mitigation method takes a sequence of short-exposure frames of a static scene and outputs a single restored image. A block-matching registration algorithm is used to provide geometric correction for each of the individual input frames. The registered frames are then averaged, and the average image is processed with a Wiener filter to provide deconvolution. An important aspect of the proposed method lies in how we model the degradation point spread function (PSF) for the purposes of Wiener filtering. We use a parametric model that takes into account the level of geometric correction achieved during image registration. This is unlike any method we are aware of in the literature. By matching the PSF to the level of registration in this way, the Wiener filter is able to fully exploit the reduced blurring achieved by registration. We also describe a method for estimating the atmospheric coherence diameter (or Fried parameter) from the estimated motion vectors. We provide a detailed performance analysis that illustrates how the key tuning parameters impact system performance. The proposed method is relatively simple computationally, yet it has excellent performance in comparison with state-of-the-art benchmark methods in our study.

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Blind image quality metrics for optimal speckle image reconstruction in horizontal imaging scenarios

Cited by 10 publications

References 20 publications

Objective Image-Quality Assessment for High-Resolution Photospheric Images by Median Filter-Gradient Similarity

Objective Image-Quality Assessment for High-Resolution Photospheric Images by Median Filter-Gradient Similarity

A new performance metric for hybrid adaptive optics systems

Block matching and Wiener filtering approach to optical turbulence mitigation and its application to simulated and real imagery with quantitative error analysis

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