Depth from HDR: Depth Induction or Increased Realism?

Many people who first see a high dynamic range (HDR) display get the impression that it is a 3D display, even though it does not produce any binocular depth cues. Possible explanations of this effect include contrast-based depth induction and the increased re-alism due to the high brightness and contrast that makes an HDR display “like looking through a window”. In this paper we test both of these hypotheses by comparing the HDR depth illusion to real binocular depth cues using a carefully calibrated HDR stereo-scope. We confirm that contrast-based depth induction exists, but it is a vanishingly weak depth cue compared to binocular depth cues. We also demonstrate that for some observers, the increased con-trast of HDR displays indeed increases the realism. However, it is highly observer-dependent whether reduced, physically correct, or exaggerated contrast is perceived as most realistic, even in the pres-ence of the real-world reference scene. Similarly, observers differ in whether reduced, physically correct, or exaggerated stereo 3D is perceived as more realistic. To accommodate the binocular depth perception and realism concept of most observers, display technolo-gies must offer both HDR contrast and stereo personalization

Learning GAN-based Foveated Reconstruction to Recover Perceptually Important Image Features

A foveated image can be entirely reconstructed from a sparse set of samples distributed according to the retinal sensitivity of the human visual system, which rapidly decreases with increasing eccentricity. The use of Generative Adversarial Networks has recently been shown to be a promising solution for such a task, as they can successfully hallucinate missing image information. As in the case of other supervised learning approaches, the definition of the loss function and the training strategy heavily influence the quality of the output. In this work,we consider the problem of efficiently guiding thetraining of foveated reconstruction techniques such that they are more aware of the capabilities and limitations of the human visual system, and thus can reconstruct visually important image features. Our primary goal is to make the training procedure less sensitive to distortions that humans cannot detect and focus on penalizing perceptually important artifacts. Given the nature of GAN-based solutions, we focus on the sensitivity of human vision to hallucination in case of input samples with different densities. We propose psychophysical experiments, a dataset, and a procedure for training foveated image reconstruction. The proposed strategy renders the generator network flexible by penalizing only perceptually important deviations in the output. As a result, the method emphasized the recovery of perceptually important image features. We evaluated our strategy and compared it with alternative solutions by using a newly trained objective metric, a recent foveated video quality metric, and user experiments. Our evaluations revealed significant improvements in the perceived image reconstruction quality compared with the standard GAN-based training approach

Intrapartum PCR assay is a fast and efficient screening method for Group B Streptococcus detection in pregnancy

Objectives: The aim of the study is to verify the usefulness of a real-time polymerase chain reaction versus the culture forante- and intrapartum group B Streptococcus maternal colonization (GBS) and prevalence of discordance during the periodbetween an antepartum screening and delivery.Material and methods: The study involved 106 pregnant women aged 18 to 39 years. Rectovaginal samples were collectedaccording to CDC guidelines at 35–37 weeks of gestation as well as in the first stage of labour, during physical examinationand were analyzed using two independent diagnostic methods: microbiological culture with standard culture andpolymerase chain reaction with real-time assay.Results: The discordance between antenatal and intrapartum GBS prevalence has been demonstrated as well as differencesassociated with diagnostic strategies, culture and PCR.Conclusions: Intrapartum detection of GBS colonization using culture or Real-Time PCR assay as well, regardless of antenatalscreening test for GBS, is very useful in identifying women who require implementation or withdrawal from prophylacticintrapartum antibiotic therapy. Real-Time PCR is a quick efficient method for GBS screening in pregnant women, whichcan be even applied during labor due to its short time of analyzing and high sensitivity and specificity. The above fact mayindicate the need to perform the GBS test in the intrapartum period in all pregnant GBS negative women using PCR assayas a more adequate diagnostic method as the procedure could reduce the risk of a neonatal GBS infection subsequentlyto a prophylactic antibiotic therapy in women with an intrapartum positive GBS

Image Registration for Multi-exposure High Dynamic Range Image Acquisition

We present a fully automatic method for eliminating misalignments between a sequence of hand-held photographs taken at different exposures. The key component of the technique is the SIFT method that is employed to search for key-points (or feature-points) in consecutive images. The key-points are used to find matrices, that transform a set of images to a single coordinate system and eliminate any global misalignments (including general planar homography). We employ this technique to capture high dynamic range images from a set of photographs taken at different exposures, wheremisalignments can cause blurring and artifacts, and prevent achieving high quality HDR images. The proposed alignment technique works well for over- and under-exposed images and is not sensitive to an image content. We present our implementation of the technique and the results of tests made for variety of photographs

Selected Problems of High Dynamic Range Video Compression and GPU-based Contrast Domain Tone Mapping

The main goal of High Dynamic Range Imaging (HDRI) is precise reproduction of real world appearance in terms of intensity levels and color gamut at all stages of image and video processing from acquisition to display. In our work, we investigate the problem of lossy HDR image and video compression and provide a number of novel solutions, which are optimized for storage efficiency or backward compatibility with existing compression standards. To take advantage of HDR information even for traditional low-dynamic range displays, we design tone mapping algorithms, which adjust HDR contrast ranges in a scene to those available in typical display devices

High Dynamic Range Imaging Pipeline: Perception-Motivated Representation of Visual Content

The advances in high dynamic range (HDR) imaging, especially in the display and camera technology, have a significant impact on the existing imaging systems. The assumptions of the traditional low-dynamic range imaging, designed for paper print as a major output medium, are ill suited for the range of visual material that is shown on modern displays. For example, the common assumption that the brightest color in an image is white can be hardly justified for high contrast LCD displays, not to mention next generation HDR displays, that can easily create bright highlights and the impression of self-luminous colors. We argue that high dynamic range representation can encode images regardless of the technology used to create and display them, with the accuracy that is only constrained by the limitations of the human eye and not a particular output medium. To facilitate the research on high dynamic range imaging, we have created a software packag