JPEG-HDR: a Backwards-Compatible, High Dynamic Range Extension to JPEG
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Ultra HD Playout & Delivery
Ultra HD Playout & Delivery SOLUTION BRIEF The next major advancement in television has arrived: Ultra HD. By 2020 more than 40 million consumers around the world are projected to be watching close to 250 linear UHD channels, a figure that doesn’t include VOD (video-on-demand) or OTT (over-the-top) UHD services. A complete UHD playout and delivery solution from Harmonic will help you to meet that demand. 4K UHD delivers a screen resolution four times that of 1080p60. Not to be confused with the 4K digital cinema format, a professional production and cinema standard with a resolution of 4096 x 2160, UHD is a broadcast and OTT standard with a video resolution of 3840 x 2160 pixels at 24/30 fps and 8-bit color sampling. Second-generation UHD specifications will reach a frame rate of 50/60 fps at 10 bits. When combined with advanced technologies such as high dynamic range (HDR) and wide color gamut (WCG), the home viewing experience will be unlike anything previously available. The expected demand for UHD content will include all types of programming, from VOD movie channels to live global sporting events such as the World Cup and Olympics. UHD-native channel deployments are already on the rise, including the first linear UHD channel in North America, NASA TV UHD, launched in 2015 via a partnership between Harmonic and NASA’s Marshall Space Flight Center. The channel highlights incredible imagery from the U.S. space program using an end-to-end UHD playout, encoding and delivery solution from Harmonic. The Harmonic UHD solution incorporates the latest developments in IP networking and compression technology, including HEVC (High- Efficiency Video Coding) signal transport and HDR enhancement. -
Senior Tech Tuesday 11 Iphone Camera App Tour
More Info: Links.SeniorTechClub.com/Tuesdays Welcome to Senior Tech Tuesday Live: 1/19/2021 Photography Series Tour of the Camera App Don Frederiksen Our Tuesday Focus ➢A Tour of the Camera App - Getting Beyond Point & Shoot ➢Selfies ➢Flash ➢Zoom ➢HDR is Good ➢What is a Live Photo ➢Focus & Exposure ➢Filters ➢Better iPhone Photography Tip ➢What’s Next www.SeniorTechClub.com Zoom Setup Zoom Speaker View Computer iPad or laptop Laptop www.SeniorTechClub.com Our Learning Tools ◦ Zoom Video Platform ◦ Slides – Downloadable from class page ◦ Demonstrations ◦ Your Questions ◦ “Hey Don” or Chat ◦ Email: [email protected] ◦ Online Class Page at: Links.SeniorTechClub.com/STT11 ◦ Tuesdays Page for Future Topics Links.SeniorTechClub.com/tuesdays www.SeniorTechClub.com Our Class Page Find our class page at: ◦ Links.SeniorTechClub.com/STT11 ◦ Bottom of the Tuesday page Purpose of the Class Page ◦ Relevant Information ◦ Fill in gaps from the online session ◦ Participate w/o being online www.SeniorTechClub.com Tour of our Class Page Slide Deck Video Archive Links & Resources Recipes & Nuggets www.SeniorTechClub.com A Tour of the Camera App Poll www.SeniorTechClub.com A Tour of the Camera App - Classic www.SeniorTechClub.com A Tour of the Camera App - New www.SeniorTechClub.com Switch Camera - Selfie Reminder: Long Press Shortcut Zoom Two kinds of zoom on iPhones Optical Zoom via a Lens Zoom Digital Zoom via a Pinch Better to zoom with your feet then digital Zoom Digital Zoom – Pinch Screen in or out Optical ◦ If your iPhone has more than one lens, tap: ◦ .5x or 1x or 2x (varies by model) Flash Focus & Exposure HDR Photos High Dynamic Range iPhone takes multiple photos to balance shadows and highlights. -
JPEG Compatible Coding of High Dynamic Range Imagery Using Tone Mapping Operators
JPEG Compatible Coding of High Dynamic Range Imagery using Tone Mapping Operators Min Chen1, Guoping Qiu1, Zhibo Chen2 and Charles Wang2 1School of Computer Science, The University of Nottingham, UK 2Thomson Broadband R&D (Beijing) Co., Ltd, China Abstract. In this paper, we introduce a new method for HDR imaging remain. For example, to display HDR compressing high dynamic range (HDR) imageries. Our images in conventional CRT or print HDR image on method exploits the fact that tone mapping is a necessary paper, the dynamic range of the image has to be operation for displaying HDR images on low dynamic compressed or the HDR image has to be tone mapped. range (LDR) reproduction media and seamlessly Even though there has been several tone mapping integrates tone mapping with a well-established image methods in the literature [3 - 12], non so far can compression standard to produce a HDR image universally produce satisfactorily results. Another huge compression technique that is backward compatible with challenge is efficient storage of HDR image. Compared established standards. We present a method to handle with conventional 24-bit/pixel images, HDR image is 96 color information so that HDR image can be gracefully bits/pixel and data is stored as 32-bit floating-point reconstructed from the tone mapped LDR image and numbers instead of 8-bit integer numbers. The data rate extra information stored with it. We present experimental using lossless coding, e.g, in OpenEXR [15], will be too results to demonstrate that the proposed technique works high especially when it comes to HDR video. -
LIVE 15 Better Iphone Photos – Beyond Point
Welcome to Senior Tech Club Please Stand By! LIVE! We will begin at With Don Frederiksen 10 AM CDT Welcome to Senior Tech Club LIVE! With Don Frederiksen www.SeniorTechClub.com Today’s LIVE! Focus ➢The iPhone has a Great Camera ➢Getting Beyond Point & Click ➢Rule of Thirds for Composition ➢HDR is Good ➢What is a Live Photo ➢Video Mode ➢Pano ➢What’s Next Questions: Text to: 612-930-2226 or YouTube Chat Housekeeping & Rules ➢Pretend that we are sitting around the kitchen table. ➢I Cannot See You!! ➢I Cannot Hear You!! ➢Questions & Comments ➢Chat at the YouTube Site ➢Send me a text – 612-930-2226 ➢Follow-up Question Email: [email protected] Questions: Text to: 612-930-2226 or YouTube Chat The iPhone puts a Good Camera in your pocket Questions: Text to: 612-930-2226 or YouTube Chat The iPhone puts a Good Camera in your pocket For Inspiration: Ippawards.com/gallery Questions: Text to: 612-930-2226 or YouTube Chat Typical iPhone Photographer Actions: 1. Tap Camera icon 2. Tap Shutter Questions: Text to: 612-930-2226 or YouTube Chat The iPhone puts a Good Camera in your pocket Let’s Use it to the Max Questions: Text to: 612-930-2226 or YouTube Chat The Camera App Questions: Text to: 612-930-2226 or YouTube Chat Rule of Thirds Questions: Text to: 612-930-2226 or YouTube Chat Rule of Thirds Google Search of Photography Rule of Thirds Images Questions: Text to: 612-930-2226 or YouTube Chat iPhone Grid Support Questions: Text to: 612-930-2226 or YouTube Chat Turn on the Grid Launch the Settings app. -
High Dynamic Range Video
High Dynamic Range Video Karol Myszkowski, Rafał Mantiuk, Grzegorz Krawczyk Contents 1 Introduction 5 1.1 Low vs. High Dynamic Range Imaging . 5 1.2 Device- and Scene-referred Image Representations . ...... 7 1.3 HDRRevolution ............................ 9 1.4 OrganizationoftheBook . 10 1.4.1 WhyHDRVideo? ....................... 11 1.4.2 ChapterOverview ....................... 12 2 Representation of an HDR Image 13 2.1 Light................................... 13 2.2 Color .................................. 15 2.3 DynamicRange............................. 18 3 HDR Image and Video Acquisition 21 3.1 Capture Techniques Capable of HDR . 21 3.1.1 Temporal Exposure Change . 22 3.1.2 Spatial Exposure Change . 23 3.1.3 MultipleSensorswithBeamSplitters . 24 3.1.4 SolidStateSensors . 24 3.2 Photometric Calibration of HDR Cameras . 25 3.2.1 Camera Response to Light . 25 3.2.2 Mathematical Framework for Response Estimation . 26 3.2.3 Procedure for Photometric Calibration . 29 3.2.4 Example Calibration of HDR Video Cameras . 30 3.2.5 Quality of Luminance Measurement . 33 3.2.6 Alternative Response Estimation Methods . 33 3.2.7 Discussion ........................... 34 4 HDR Image Quality 39 4.1 VisualMetricClassification. 39 4.2 A Visual Difference Predictor for HDR Images . 41 4.2.1 Implementation......................... 43 5 HDR Image, Video and Texture Compression 45 1 2 CONTENTS 5.1 HDR Pixel Formats and Color Spaces . 46 5.1.1 Minifloat: 16-bit Floating Point Numbers . 47 5.1.2 RGBE: Common Exponent . 47 5.1.3 LogLuv: Logarithmic encoding . 48 5.1.4 RGB Scale: low-complexity RGBE coding . 49 5.1.5 LogYuv: low-complexity LogLuv . 50 5.1.6 JND steps: Perceptually uniform encoding . -
High Dynamic Range Image Compression Based on Visual Saliency Jin Wang,1,2 Shenda Li1 and Qing Zhu1
SIP (2020), vol. 9, e16, page 1 of 15 © The Author(s), 2020 published by Cambridge University Press in association with Asia Pacific Signal and Information Processing Association. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, providedthesameCreative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use. doi:10.1017/ATSIP.2020.15 original paper High dynamic range image compression based on visual saliency jin wang,1,2 shenda li1 and qing zhu1 With wider luminance range than conventional low dynamic range (LDR) images, high dynamic range (HDR) images are more consistent with human visual system (HVS). Recently, JPEG committee releases a new HDR image compression standard JPEG XT. It decomposes an input HDR image into base layer and extension layer. The base layer code stream provides JPEG (ISO/IEC 10918) backward compatibility, while the extension layer code stream helps to reconstruct the original HDR image. However, thismethoddoesnotmakefulluseofHVS,causingwasteofbitsonimperceptibleregionstohumaneyes.Inthispaper,avisual saliency-based HDR image compression scheme is proposed. The saliency map of tone mapped HDR image is first extracted, then it is used to guide the encoding of extension layer. The compression quality is adaptive to the saliency of the coding region of the image. Extensive experimental results show that our method outperforms JPEG XT profile A, B, C and other state-of-the-art methods. -
High Dynamic Range Metadata for Apple Devices (Preliminary)
High Dynamic Range Metadata For Apple Devices (Preliminary) " Version 0.9 May 31, 2019 ! Copyright © 2019 Apple Inc. All rights reserved. Apple, the Apple logo and QuickTime are trademarks of Apple Inc., registered in the U.S. and other countries. Dolby, Dolby Vision, and the double-D symbol are trademarks of Dolby Laboratories. 1" Introduction 3 Dolby Vision™ 4 HDR10 6 Hybrid Log-Gamma (HLG) 8 References 9 Document Revision History 10 ! Copyright © 2019 Apple Inc. All rights reserved. Apple, the Apple logo and QuickTime are trademarks of Apple Inc., registered in the U.S. and other countries. Dolby, Dolby Vision, and the double-D symbol are trademarks of Dolby Laboratories. 2" Introduction This document describes the metadata and constraints for High Dynamic Range (HDR) video stored in a QuickTime Movie or ISO Base Media File required for proper display on Apple Plat- forms. Three types of HDR are detailed. 1. Dolby Vision™ 2. HDR10 3. Hybrid Log-Gamma (HLG) Note: The QuickTime Movie File Format Specification and the ISO Base Media File Format Specification use different terminology for broadly equivalent concepts: atoms and boxes; sam- ple descriptions and sample entries. This document uses the former specification's terminolo- gies without loss of generality. This document covers file-based workflows, for HLS streaming requirements go to: https://developer.apple.com/documentation/http_live_streaming/hls_authoring_specification_- for_apple_devices ! Copyright © 2019 Apple Inc. All rights reserved. Apple, the Apple logo and QuickTime are trademarks of Apple Inc., registered in the U.S. and other countries. Dolby, Dolby Vision, and the double-D symbol are trademarks of Dolby Laboratories. -
Tone Reproduction: a Perspective from Luminance-Driven Perceptual Grouping
International Journal of Computer Vision c 2006 Springer Science + Business Media, Inc. Manufactured in The Netherlands. DOI: 10.1007/s11263-005-3846-z Tone Reproduction: A Perspective from Luminance-Driven Perceptual Grouping HWANN-TZONG CHEN Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan; Department of CSIE, National Taiwan University, Taipei 106, Taiwan [email protected] TYNG-LUH LIU Institute of Information Science, Academia Sinica, Nankang, Taipei 115, Taiwan [email protected] CHIOU-SHANN FUH Department of CSIE, National Taiwan University, Taipei 106, Taiwan [email protected] Received June 16, 2004; Revised May 24, 2005; Accepted June 29, 2005 First online version published in January, 2006 Abstract. We address the tone reproduction problem by integrating the local adaptation effect with the consistency in global contrast impression. Many previous works on tone reproduction have focused on investigating the local adaptation mechanism of human eyes to compress high-dynamic-range (HDR) luminance into a displayable range. Nevertheless, while the realization of local adaptation properties is not theoretically defined, exaggerating such effects often leads to unnatural visual impression of global contrast. We propose to perceptually decompose the luminance into a small number of regions that sequentially encode the overall impression of an HDR image. A piecewise tone mapping can then be constructed to region-wise perform HDR compressions, using local mappings constrained by the estimated global perception. Indeed, in our approach, the region information is used not only to practically approximate the local properties of luminance, but more importantly to retain the global impression. Besides, it is worth mentioning that the proposed algorithm is efficient, and mostly does not require excessive parameter fine-tuning. -
Chapter 20 Photographic Films
P d A d R d T d 6 IMAGING DETECTORS CHAPTER 20 PHOTOGRAPHIC FILMS Joseph H . Altman Institute of Optics Uniy ersity of Rochester Rochester , New York 20 . 1 GLOSSARY A area of microdensitometer sampling aperture a projective grain area D optical transmission density D R reflection density DQE detective quantum ef ficiency d ( m ) diameter of microdensitometer sampling aperture stated in micrometers E irradiance / illuminance (depending on context) & Selwyn granularity coef ficient g absorbance H exposure IC information capacity M modulation M θ angular magnification m lateral magnification NEQ noise equivalent quanta P ( l ) spectral power in densitometer beam Q 9 ef fective Callier coef ficient q exposure stated in quanta / unit area R reflectance S photographic speed S ( l ) spectral sensitivity S / N signal-to-noise ratio of the image 20 .3 20 .4 IMAGING DETECTORS T transmittance T ( … ) modulation transfer factor at spatial frequency … t duration of exposure WS ( … ) value of Wiener (or power) spectrum for spatial frequency … g slope of D-log H curve … spatial frequency r ( l ) spectral response of densitometer s ( D ) standard deviation of density values observed when density is measured with a suitable sampling aperture at many places on the surface s ( T ) standard deviation of transmittance f ( τ ) Autocorrelation function of granular structure 20 . 2 STRUCTURE OF SILVER HALIDE PHOTOGRAPHIC LAYERS The purpose of this chapter is to review the operating characteristics of silver halide photographic layers . Descriptions of the properties of other light-sensitive materials , such as photoresists , can be found in Ref . 4 . Silver-halide-based photographic layers consist of a suspension of individual crystals of silver halide , called grains , dispersed in gelatin and coated on a suitable ‘‘support’’ or ‘‘base . -
Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection
applied sciences Article Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection Ho-Hyoung Choi 1 , Hyun-Soo Kang 2,* and Byoung-Ju Yun 3,* 1 Advanced Dental Device Development Institute, School of Dentistry, Kyungpook National University, 2177, Dalgubeol-daero, Jung-gu, Daegu 41940, Korea; [email protected] 2 School of Information and Communication Engineering, College of Electrical and Computer Engineering, Chungbuk National University, 1, Chungdae-ro, Seowon-gu, Cheongju-si, Chungcheongbuk-do 28644, Korea 3 School of Electronics Engineering, IT College, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Korea * Correspondence: [email protected] (H.-S.K.); [email protected] (B.-J.Y.); Tel.: +82-53-950-7329 (B.-J.Y.) Received: 9 September 2019; Accepted: 29 October 2019; Published: 1 November 2019 Abstract: One of the significant qualities of the human vision, which differentiates it from computer vision, is so called attentional control, which is the innate ability of our human eyes to select what visual stimuli to pay attention to at any moment in time. In this sense, the visual salience detection model, which is designed to simulate how the human visual system (HVS) perceives objects and scenes, is widely used for performing multiple vision tasks. This model is also in high demand in the tone mapping technology of high dynamic range images (HDRIs). Another distinct quality of the HVS is that our eyes blink and adjust brightness when objects are in their sight. Likewise, HDR imaging is a technology applied to a camera that takes pictures of an object several times by repeatedly opening and closing a camera iris, which is referred to as multiple exposures. -
Neuromorphic Camera Guided High Dynamic Range Imaging
Neuromorphic Camera Guided High Dynamic Range Imaging Jin Han1 Chu Zhou1 Peiqi Duan2 Yehui Tang1 Chang Xu3 Chao Xu1 Tiejun Huang2 Boxin Shi2∗ 1Key Laboratory of Machine Perception (MOE), Dept. of Machine Intelligence, Peking University 2National Engineering Laboratory for Video Technology, Dept. of Computer Science, Peking University 3School of Computer Science, Faculty of Engineering, University of Sydney Abstract Conventional camera Reconstruction of high dynamic range image from a sin- gle low dynamic range image captured by a frame-based Intensity map guided LDR image HDR network conventional camera, which suffers from over- or under- 퐼 exposure, is an ill-posed problem. In contrast, recent neu- romorphic cameras are able to record high dynamic range scenes in the form of an intensity map, with much lower Intensity map spatial resolution, and without color. In this paper, we pro- 푋 pose a neuromorphic camera guided high dynamic range HDR image 퐻 imaging pipeline, and a network consisting of specially Neuromorphic designed modules according to each step in the pipeline, camera which bridges the domain gaps on resolution, dynamic range, and color representation between two types of sen- Figure 1. An intensity map guided HDR network is proposed to sors and images. A hybrid camera system has been built fuse the LDR image from a conventional camera and the intensity to validate that the proposed method is able to reconstruct map captured by a neuromorphic camera, to reconstruct an HDR quantitatively and qualitatively high-quality high dynamic image. range images by successfully fusing the images and inten- ing attention of researchers. Neuromorphic cameras have sity maps for various real-world scenarios. -
Internationa Design Journal Final2.Docx
Design Issues International Design Journal, Vol.3 Issue 3 Tonal quality and dynamic range in digital cameras Dr. Manal Eissa Assistant professor, Photography, Cinema and TV dept., Faculty of Applied Arts, Helwan University, Egypt Abstract: The diversity of display technologies and introduction of high dynamic range imagery introduces the necessity of studying images of radically different dynamic ranges. Current quality assessment exposure metric systems in digital cameras are not suitable for this task, as they do not respond to all brightness variations in the original scene limited by its dynamic range. The research investigates high dynamic range (HDR) technique and how to approach high tonal quality images compared to the original scene range of brightness, it presents advantages of using Raw file format in storing digital images and using curves to adjust tones by using descriptive method, then An Experiment was carried out using HDR technique as an attempt to achieve higher tonal quality in the final image. The paper concluded that HDR photography is one of the best working techniques to work with when capturing images with digital camera in scenes containing variable brightness levels than the digital camera sensor ability to record AS outdoors and landscape scenes using specific steps shown in the paper and using raw file format to approach best results. Also, the researcher believes that a further work should be carried out on more enhancements in digital camera tonal range response using sophisticated camera sensors. Keywords: Image quality metrics, HDR (high dynamic range images), LDR (low Dynamic range images), Visual perception, and Tone reproduction. standard file format such as a JPEG which is Introduction Images captured with digital cameras can the default for most digital cameras.