<p>Motion blur is a form of image quality degradation, showing as content in the image smearing and not looking sharp. It is usually seen in photography due to relative motion between the camera and the scene (either camera moves or objects in the scene move). It is also seen in human vision systems, primarily on digital displays.</p> <p><br></p> <p>It is often desired to remove motion blurriness from images. Numerous works have been put into reducing motion blur <em>after</em> the image has been formed, e.g., for camera-captured ones. Unlike post-processing methods, we take the approach to prevent/minimize motion blur for both human and camera observation by pre-processing the source image. The pre-processed images are supposed to look sharp upon blurring. Note that, only pre-processing methods can deal with human-observed blurriness since the imagery can't be modified after it is formed on the retina.</p> <p><br></p> <p>Pre-processing methods face more fundamental challenges than post-processing ones. A problem inherent to such methods is the appearance of ringing artifacts which are intensity oscillations reducing the quality of the observed image. We found that these ringing artifacts have a fundamental cause rooted in the blur kernel. The blur kernel usually have very low amplitudes in some frequencies, significantly attenuating the signal intensity in these frequencies when it convolves an image. Pre-processing methods can usually reconstruct the targeted image to the observer but inevitably lose energy in those frequencies, appearing as artifacts. To address the artifact issue, we present a few approaches: (a) aligning the image content and the kernel in the frequency domain, and (b) redistributing their intensity variations elsewhere in the image. We demonstrate the effectiveness of our method in a working prototype, in simulation, and with a user study.</p>

Yes / Purpose: To determine presenting visual acuity levels and explore the factors associated with failing vision screening in a multi-ethnic population of UK children aged 4–5 years. Methods: Visual acuity (VA) using the logMAR Crowded Test was measured in 16,541 children in a population-based vision screening programme. Referral for cycloplegic examination was based on national recommendations (>0.20logMAR in one or both eyes). Presenting visual impairment (PVI) was defined as VA >0.3logMAR in the better eye. Multivariable logistic regression was used to assess the association of ethnicity, maternal, and early-life factors with failing vision screening and PVI in participants of the Born in Bradford birth cohort. Results: In total, 2467/16,541 (15%) failed vision screening, 732 (4.4%) had PVI. Children of Pakistani (OR: 2.49; 95% CI: 1.74–3.60) and other ethnicities (OR: 2.00; 95% CI: 1.28–3.12) showed increased odds of PVI compared to white children. Children born to older mothers (OR: 1.63; 95% CI: 1.19–2.24) and of low birth weight (OR: 1.52; 95% CI: 1.00–2.34) also showed increased odds. Follow-up results were available for 1068 (43.3%) children, 993 (93%) were true positives; 932 (94%) of these had significant refractive error. Astigmatism (>1DC) (44%) was more common in children of Pakistani ethnicity and hypermetropia (>3.0DS) (27%) in white children (Fisher’s exact, p < 0.001). Conclusions: A high prevalence of PVI is reported. Failing vision screening and PVI were highly associated with ethnicity. The positive predictive value of the vision screening programme was good, with only 7% of children followed up confirmed as false positives. / National Institute for Health Research Post-Doctoral Fellowship Award (PDF-2013-06-050); The Born in Bradford study presents independent research commissioned by the National Institute for Health Research Collaboration for Applied Health Research and Care (NIHR CLAHRC) and the Programme Grants for Applied Research funding scheme (RP-PG-0407-10044).