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  • The Automotive Mirror-Replacement Technology based on ISO 16505

    This contribution presents a discussion of automotive mirrorreplacement by camera monitor systems (CMS). This is a growing research and development field. Such systems can be used to improve factors of the indirect vision of the driver, to improve the aerodynamics and to optimize the fuel economy of new vehicles. Besides the potential benefits of such a system, there are also potential challenges discussed in this contribution. The normative framework of the new standard ISO 16505:2015 in combination with the latest version of UN Regulation No. 46 enables the replacement of mandatory rear-view mirrors by CMS for vehicles in series production. Based on the characteristics of conventional mirrors, a CMS has to be designed for comparable functionality. This includes the real time behavior, the system resolution, and the dimensions of the displayed object and field of view. In this chapter, beginning with system requirements, incorporating additional standards and regulations, different CMS architectures are discussed. The final subsection presents a system design based on ISO 16505:2015 including selected real values and a description of camera, display, and image processing components of a CMS.

  • R-REC-BT.2020-2-201510.pdf

    Parameter values for ultra-high definition television systems for production and international programme exchange

  • R-REC-BT.2100-2-201807.pdf

    Image parameter values for high dynamic range television for use in production and international programme exchange

  • ICRU Report 54 The Assessment of Image Quality

    During the past two decades, the field of medical imaging has achieved dramatic improvements in imaging system capability with accompanying increases in system complexity. Much of this progress has been fueled by advances in computing technology and the widespread adoption of digital techniques for data acquisition, processing and display. Although every branch of medical imaging has been significantly affected, the most striking examples ofthis revolution are x-ray computed tomography and magnetic resonance imaging. Fortunately, a consensus on quantitative measurement methodology for assessing diagnostic imaging technologies has been gradually emerging. It has grown out of the recognition of common features among imaging modalities that allows their limitations to be understood within the framework of statistical decision analysis.

  • IEC 62676-5-2018 Data specifications and image quality performance

    IEC Technical Committee 79 in charge of alarm and electronic security systems together with many governmental organizations, test houses and equipment manufacturers has defined a common framework for video surveillance transmission in order to achieve interoperability between products. The purpose of this part of IEC 62676 is to specify representation and measuring methods of performance values to be described in materials such as instruction manuals, brochures and specifications of video surveillance camera equipment, and provide convenience for users, installers, integrators and maintenance companies, etc.

  • ISO 16505-2019 Road vehicles — Ergonomic and performance aspects of Camera Monit

    The purpose of this document is to give minimum safety, ergonomic, and performance requirements and test methods for Camera Monitor Systems (CMS) to replace mandatory inside and outside rearview mirrors for road vehicles (e.g. classes I to IV as defined in UN Regulation No. 46). This document can follow updates of referred national regulations that influence the included contents.

  • CIE_15-2004_Colorimetry.pdf

    This publication provides the recommendations of the CIE concerning basic colorimetry. Specifically, it includes the use of the standard illuminants and the standard colorimetric observers; the reference standard for reflectance; the illuminating and viewing conditions; the calculation of tristimulus values, chromaticity coordinates, colour spaces and colour differences; and the various other colorimetric practices and formulae.

  • Development of a Perceptually Calibrated Objective Metric for Exposure Quality

    This study aims at developing an image quality metric for exposure quality, with a transform to just noticeable differences (JNDs) of quality in pictorial scenes. Such a perceptually calibrated exposure metric would allow the prediction of overall image quality by combining exposure with other image attributes. Eight pictorial images were used in the study, and twenty-one observers participated in the subjective evaluation using a softcopy quality ruler method defined in ISO 20462 Part 3. The image simulation path involved seven levels of exposure manipulation, together with two variations in tone mapping algorithms (a global tone mapping algorithm and a local tone mapping algorithm). For each pictorial scene a second image was captured with an exposure target in the scene, allowing the measurement of the scene exposure level. The results showed that an objective metric based on the green channel intensity of the exposure target could be used to predict the optimal exposure level and the quality falloff due to exposure error.

  • Development of a perceptually calibrated objective metric of noise

    A system simulation model was used to create scene-dependent noise masks that reflect current performance of mobile phone cameras. Stimuli with different overall magnitudes of noise and with varying mixtures of red, green, blue, and luminance noises were included in the study. Eleven treatments in each of ten pictorial scenes were evaluated by twenty observers using the softcopy ruler method. In addition to determining the quality loss function in just noticeable differences (JNDs) for the average observer and scene, transformations for different combinations of observer sensitivity and scene susceptibility were derived. The psychophysical results were used to optimize an objective metric of isotropic noise based on system noise power spectra (NPS), which were integrated over a visual frequency weighting function to yield perceptually relevant variances and covariances in CIE L*a*b* space. Because the frequency weighting function is expressed in terms of cycles per degree at the retina, it accounts for display pixel size and viewing distance effects, so application-specific predictions can be made. Excellent results were obtained using only L* and a* variances and L*a* covariance, with relative weights of 100, 5, and 12, respectively. The positive a* weight suggests that the luminance (photopic) weighting is slightly narrow on the long wavelength side for predicting perceived noisiness. The L*a* covariance term, which is normally negative, reflects masking between L* and a* noise, as confirmed in informal evaluations. Test targets in linear sRGB and rendered L*a*b* spaces for each treatment are available at http://www.aptina.com/ImArch/ to enable other researchers to test metrics of their own design and calibrate them to JNDs of quality loss without performing additional observer experiments. Such JND-calibrated noise metrics are particularly valuable for comparing the impact of noise and other attributes, and for computing overall image quality.

  • Color in Computer Vision:Fundamentals and Applications

    Visual information is our most natural source ofinformation and communication. Apart from human vision, visual information plays a vital and indispensable role in society and is the nucleus of current communication frameworks such as the World Wide Web and mobile phones. With the ever-growing production, use, and exploitation of digital visual information (e.g., documents, websites, images, videos, and movies), a visual overflow will occur, and hence demands are urgent for the (automatic) understanding of visual information. Moreover, as digital visual information is nowadays available in color format, there is the irreversible necessity for the understanding of visual color information. Computer vision deals with the understanding of visual information. Although color became a central topic in various disciplines (ranging from mathematics and physics to the humanities and art) quite early on, in the field of computer vision it has emerged only recently. We take on the challenge of providing a substantial set of tools for image understanding from a color perspective. The central topic of this book is to present color theories, representation models, and computational methods that are essential for image understanding in the field of computer vision.

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