scholarly journals Relative Impact of Key Rendering Parameters on Perceived Quality of VR Imagery Captured by the Facebook Surround 360 Camera

Frameless ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 39-44
Author(s):  
Nora Pfund ◽  
◽  
Nitin Sampat ◽  
J. A. Stephen Viggiano ◽  
◽  
...  
Keyword(s):  
Image Quality ◽  
Open Source ◽  
Dynamic Range ◽  
Computer Hardware ◽  
Recent Experience ◽  
Relative Impact ◽  
High Quality ◽  
Geometric Calibration ◽  
Black Level

High quality, 360 capture for Cinematic VR is a relatively new and rapidly evolving technology. The field demands very high quality, distortion- free 360 capture which is not possible with cameras that depend on fish- eye lenses for capturing a 360 field of view. The Facebook Surround 360 Camera, one of the few “players” in this space, is an open-source license design that Facebook has released for anyone that chooses to build it from off-the-shelf components and generate 8K stereo output using open-source licensed rendering software. However, the components are expensive and the system itself is extremely demanding in terms of computer hardware and software. Because of this, there have been very few implementations of this design and virtually no real deployment in the field. We have implemented the system, based on Facebook’s design, and have been testing and deploying it in various situations; even generating short video clips. We have discovered in our recent experience that high quality, 360 capture comes with its own set of new challenges. As an example, even the most fundamental tools of photography like “exposure” become difficult because one is always faced with ultra-high dynamic range scenes (one camera is pointing directly at the sun and the others may be pointing to a dark shadow). The conventional imaging pipeline is further complicated by the fact that the stitching software has different effects on various as- pects of the calibration or pipeline optimization. Most of our focus to date has been on optimizing the imaging pipeline and improving the qual- ity of the output for viewing in an Oculus Rift headset. We designed a controlled experiment to study 5 key parameters in the rendering pipeline– black level, neutral balance, color correction matrix (CCM), geometric calibration and vignetting. By varying all of these parameters in a combinatorial manner, we were able to assess the relative impact of these parameters on the perceived image quality of the output. Our results thus far indicate that the output image quality is greatly influenced by the black level of the individual cameras (the Facebook cam- era comprised of 17 cameras whose output need to be stitched to obtain a 360 view). Neutral balance is least sensitive. We are most confused about the results we obtain from accurately calculating and applying the CCM for each individual camera. We obtained improved results by using the average of the matrices for all cameras. Future work includes evaluating the effects of geometric calibration and vignetting on quality.

An open-source R-package and web application for high-quality probabilistic predictions in hydrology

2021 ◽  
Author(s):  
Jason Hunter ◽  
Mark Thyer ◽  
Dmitri Kavetski ◽  
David McInerney
Keyword(s):  
Open Source ◽  
Web Application ◽  
R Package ◽  
Error Model ◽  
Objective Functions ◽  
High Quality ◽  
Wide Range ◽  
Probabilistic Error

<p>Probabilistic predictions provide crucial information regarding the uncertainty of hydrological predictions, which are a key input for risk-based decision-making. However, they are often excluded from hydrological modelling applications because suitable probabilistic error models can be both challenging to construct and interpret, and the quality of results are often reliant on the objective function used to calibrate the hydrological model.</p><p>We present an open-source R-package and an online web application that achieves the following two aims. Firstly, these resources are easy-to-use and accessible, so that users need not have specialised knowledge in probabilistic modelling to apply them. Secondly, the probabilistic error model that we describe provides high-quality probabilistic predictions for a wide range of commonly-used hydrological objective functions, which it is only able to do by including a new innovation that resolves a long-standing issue relating to model assumptions that previously prevented this broad application.  </p><p>We demonstrate our methods by comparing our new probabilistic error model with an existing reference error model in an empirical case study that uses 54 perennial Australian catchments, the hydrological model GR4J, 8 common objective functions and 4 performance metrics (reliability, precision, volumetric bias and errors in the flow duration curve). The existing reference error model introduces additional flow dependencies into the residual error structure when it is used with most of the study objective functions, which in turn leads to poor-quality probabilistic predictions. In contrast, the new probabilistic error model achieves high-quality probabilistic predictions for all objective functions used in this case study.</p><p>The new probabilistic error model and the open-source software and web application aims to facilitate the adoption of probabilistic predictions in the hydrological modelling community, and to improve the quality of predictions and decisions that are made using those predictions. In particular, our methods can be used to achieve high-quality probabilistic predictions from hydrological models that are calibrated with a wide range of common objective functions.</p>

Perceptual Quality Assessment of Low-light Image Enhancement

2021 ◽  
Vol 17 (4) ◽  
pp. 1-24
Author(s):  
Guangtao Zhai ◽  
Wei Sun ◽  
Xiongkuo Min ◽  
Jiantao Zhou
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Enhancement ◽  
Dynamic Range ◽  
State Of The Art ◽  
Perceptual Quality ◽  
Low Light ◽  
Light Image ◽  
Light Enhancement

Low-light image enhancement algorithms (LIEA) can light up images captured in dark or back-lighting conditions. However, LIEA may introduce various distortions such as structure damage, color shift, and noise into the enhanced images. Despite various LIEAs proposed in the literature, few efforts have been made to study the quality evaluation of low-light enhancement. In this article, we make one of the first attempts to investigate the quality assessment problem of low-light image enhancement. To facilitate the study of objective image quality assessment (IQA), we first build a large-scale low-light image enhancement quality (LIEQ) database. The LIEQ database includes 1,000 light-enhanced images, which are generated from 100 low-light images using 10 LIEAs. Rather than evaluating the quality of light-enhanced images directly, which is more difficult, we propose to use the multi-exposure fused (MEF) image and stack-based high dynamic range (HDR) image as a reference and evaluate the quality of low-light enhancement following a full-reference (FR) quality assessment routine. We observe that distortions introduced in low-light enhancement are significantly different from distortions considered in traditional image IQA databases that are well-studied, and the current state-of-the-art FR IQA models are also not suitable for evaluating their quality. Therefore, we propose a new FR low-light image enhancement quality assessment (LIEQA) index by evaluating the image quality from four aspects: luminance enhancement, color rendition, noise evaluation, and structure preserving, which have captured the most key aspects of low-light enhancement. Experimental results on the LIEQ database show that the proposed LIEQA index outperforms the state-of-the-art FR IQA models. LIEQA can act as an evaluator for various low-light enhancement algorithms and systems. To the best of our knowledge, this article is the first of its kind comprehensive low-light image enhancement quality assessment study.

scholarly journals Studies on the effect of MegaPixel sensor resolution on displayed image quality and relevant metrics

2020 ◽  
Vol 2020 (9) ◽  
pp. 170-1-170-10
Author(s):  
Sophie Triantaphillidou ◽  
Jan Smejkal ◽  
Edward W. S. Fry ◽  
Chuang Hsin Hung
Keyword(s):  
Image Quality ◽  
Consumer Experience ◽  
Camera Phone ◽  
High Quality ◽  
Subjective Image Quality ◽  
Star Rating ◽  
Quality Ratings ◽  
Large Numbers ◽  
Quality Scale

This paper investigates camera phone image quality, namely the effect of sensor megapixel (MP) resolution on the perceived quality of images displayed at full size on high-quality desktop displays. For the purpose, we use images from simulated cameras with different sensor MP resolutions. We employ methods recommended in the IEEE 1858 Camera Phone Image Quality (CPIQ) standard, as well as other established psychophysical paradigms, to obtain subjective image quality ratings for systems with varying MP resolution from large numbers of observers. These are subsequently used to validate image quality metrics (IQMs) relating to sharpness and resolution, including those from the CPIQ standard. Further, we define acceptable levels of quality - when changing MP resolution - for mobile phone images in Subjective Quality Scale (SQS) units. Finally, we map SQS levels to categories obtained from star-rating experiments (commonly used to rate consumer experience). Our findings draw a relationship between the MP resolution of the camera sensor and the LCD device. The chosen metrics predict quality accurately, but only the metrics proposed by CPIQ return results in calibrated JNDs in quality. We close by discussing the appropriateness of star-rating experiments for the purpose of measuring subjective image quality and metric validation.

scholarly journals Dynamic range reduction of infrared images based on adaptive equalization, stretch and compression of histogram

2021 ◽  
Vol 66 (4) ◽  
pp. 470-482
Author(s):  
S. I. Rudikov ◽  
V. Yu. Tsviatkou ◽  
A. P. Shkadarevich
Keyword(s):  
Computational Complexity ◽  
Image Quality ◽  
Dynamic Range ◽  
Histogram Equalization ◽  
Brightness Distribution ◽  
Adaptive Equalization ◽  
Infrared Images ◽  
Image Reproduction ◽  
Adaptive Histogram Equalization

The problem of reducing the dynamic range and improving the quality of infrared (IR) images with a wide dynamic range for their display on a liquid crystal matrix with 8-bit pixels is considered. To solve this problem in optoelectronic devices in real time, block algorithms based on local equalization of the histogram are widely used, taking into account their relatively low computational complexity and the possibility of taking into account local features of the brightness distribution. The basic adaptive histogram equalization algorithm provides reasonably high image quality after conversion, but may result in excessive contrast for some types of images. In a modified algorithm of adaptive histogram equalization, the contrast is limited by a threshold by truncating local maxima at the edges of the histogram. This leads, however, to a deterioration in other indicators of image quality. This disadvantage is inherent in many algorithms of local histogram equalization, along with limited control over the characteristics of image reproduction quality. To improve the quality and expand the control interval for the characteristics of the reproduction of infrared images, the article proposes an algorithm for double reduction of the dynamic range of the image with intermediate control of the shape of its histogram. This algorithm performs: preliminary reduction of the dynamic range of the image based on adaptive equalization of the histogram, control of the shape of the histogram based on its linear or nonlinear compression, linear stretching of its central part and linear stretching (compression) of its lateral parts, final reduction of the dynamic range based on linear compression of the entire histograms. The characteristics of the proposed algorithm are compared with the characteristics of known algorithms for reducing the dynamic range and improving the image quality. The dependences of the characteristics of the quality of image reproduction after a decrease in their dynamic range on the control parameters of the proposed algorithm and recommendations for their choice taking into account the computational complexity are given.

High-quality Multi-level Error Diffusion Method Employing Fuzzy Inference

2003 ◽  
Vol 7 (2) ◽  
pp. 235-243 ◽  
Author(s):  
Noriaki Suetake ◽  
◽  
Masanori Togashi ◽  
Keyword(s):  
Image Quality ◽  
Conventional Method ◽  
Fuzzy Inference ◽  
Digital Images ◽  
Diffusion Method ◽  
Error Diffusion ◽  
High Quality ◽  
Multi Level

We propose a new multi-level error diffusion method employing the fuzzy inference, which realizes half toning with high quality. In the proposed method, dissimilar textures around quantization levels, which are the cause of the low image quality and obtained by a conventional method, are decreased by using fuzzy inference. In this paper, we apply the proposed method to various standard digital images. The image quality of the result using the proposed method is higher than those of other methods without noise-add filtering, and it is almost same as them with filtering in 2 or 3 times faster processing.

scholarly journals Field Validation of GEBCO Data in the Red Sea

2019 ◽  
Vol 9 (1) ◽  
pp. 2135-2137
Keyword(s):  
Image Analysis ◽  
Open Source ◽  
Red Sea ◽  
Poor Quality ◽  
High Quality ◽  
Bathymetric Data ◽  
The Poor ◽  
Fine Resolution ◽  
Resolution Data

A comprehensive field data were collated analyzed and processed for the validation of open source bathymetry data GEBCO 30 sec arc resolution data in the selected location of the Red sea. Different software and techniques were used to verify the quality of GEBCO data in the field conditions. The image analysis using different software proves the poor quality and resolution of the GEBCO data in the nearshore areas. The analyses also brought out the complex topographical nature of the Red sea and precautions for the usage of open source bathymetric data in the nearshore areas of the Red sea, where high quality and fine resolution data required. The different statistical analyses also verified the results of image analysis. The statistical analysis also shows the poor quality and course resolution of the GEBCO 30sec resolution data in the Red sea especially nearshore areas. The study recommends hydrographic survey data for the nearshore areas, where high quality and resolution data are needed

scholarly journals Optimization of the profile and material of wire contacts for an IR photodetector

2021 ◽  
Vol 2086 (1) ◽  
pp. 012085
Author(s):  
A V Kamarchuk ◽  
D A Bauman ◽  
A I Marchenko
Keyword(s):  
High Performance ◽  
Dynamic Range ◽  
Thermal Characteristics ◽  
Practical Interest ◽  
High Sensitivity ◽  
Gold Wire ◽  
High Quality ◽  
Quality Design ◽  
Low Costs

Abstract The study is devoted to the influence of the choice of geometry and materials of wire contacts on the reflection coefficient and thermal characteristics of the photodetector and the quality of the device design. The process of diffusion of materials of wire contacts and contact pads on a photodetector crystal is investigated. The studies were carried out on samples that are rather small in size (250x250x400 um). During the experiment, 4 main types of loop geometry were selected (main loop, reverse loop, double reverse loop, long loop). The loops were formed using a gold wire 25 μm in diameter. The quality of microwelds was investigated in 3 ways: shear and pull-off tests, optical observation using a scanning electron microscope (SEM), and contact resistance measurement. The aim of the work is to create a high-quality design of an IR photodetector, which allows achieving a high sensitivity (at least 0.5 A / W), a large dynamic range (at least 40 dB) and low indicators of dark current values. The developed technology ensures high quality of the photodetector design. Due to the low costs of this technological process (wire material, the number of operations required for installation), relative to other technologies, which allows maintaining high performance in the technical component of the photodetector, the installation method may be of practical interest in production.

scholarly journals Preliminary experience with an intraoperative MRI-compatible infant headholder: technical note

2015 ◽  
Vol 15 (5) ◽  
pp. 539-543 ◽  
Author(s):  
Frederick A. Boop ◽  
Berkeley Bate ◽  
Asim F. Choudhri ◽  
Brian Burkholder ◽  
Paul Klimo
Keyword(s):  
Image Quality ◽  
Technical Note ◽  
Intraoperative Mri ◽  
Major Advance ◽  
Technical Advance ◽  
High Quality ◽  
Pin Fixation ◽  
Calvarial Defects ◽  
Neuronavigation System

The development of high-quality intraoperative MRI (iMRI) capability has offered a major advance in the care of patients with complex intracranial disease. To date, this technology has been limited by the need for pin fixation of the calvaria. The authors report their preliminary experience with an MRI-compatible horseshoe headrest that allows for the following: 1) iMRI in patients too young for pin fixation; 2) iMRI in patients with large calvarial defects; 3) the ability to move the head during iMRI surgery; and 4) the use of neuronavigation in such cases. The authors report 2 cases of infants in whom the Visius Surgical Theatre horseshoe headrest (IMRIS Inc.) was used. Image quality was equivalent to that of pin fixation. The infants suffered no skin issues. The use of neuronavigation with the system remained accurate and could be updated with the new iMRI information. The Visius horseshoe headrest offers a technical advance in iMRI technology for infants, for patients with cranial defects or prior craniotomies in whom pin fixation may not be safe, or for patients in whom the need to move the head during surgery is required. The image quality of the system remains excellent, and the ability to merge new images to the neuronavigation system is helpful.

Tone Mapping Operators Evaluation Based on High Quality Reference Images

2019 ◽  
Vol 2019 (1) ◽  
pp. 268-272
Author(s):  
Imran Mehmood ◽  
Muhammad Usman Khan ◽  
Ming Ronnier Luo ◽  
Muhammad Farhan Mughal
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Image Features ◽  
Tone Mapping ◽  
High Quality ◽  
Colour Image ◽  
Photographic Reproduction ◽  
Reference Images ◽  
High Dynamic

High Dynamic Range (HDR) imaging applications have been commonly placed recently. Several tone mapping operators (TMOs) have been developed which project the HDR radiance range to that of a display. Currently, there is no agreement on a technique for evaluation of tone mapping operators. The goal of this study is to establish a method based on reference images to evaluate the TMOs. Two psychophysical experiments were carried out for the evaluation of tone mapping operators. In the first experiment, a set of high quality images were generated to possess right extents of image features including contrast, colourfulness and sharpness. These images were further used in the second experiment as reference images to evaluate different TMOs. It was found Reinhard's photographic reproduction based on local TMO gave an overall better performance. CIELAB(2:1) and S- CIELAB metrics were also used to judge colour image quality of the same TMOs. It was found that both metrics agreed well with the visual results.

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