Color Image Reproduction of Scenes with Preferential Color Mapping and Scene-Dependent Tone Scaling
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Investigating the Effect of Color Gamut Mapping Quantitatively and Visually
Rochester Institute of Technology RIT Scholar Works Theses 5-2015 Investigating the Effect of Color Gamut Mapping Quantitatively and Visually Anupam Dhopade Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Dhopade, Anupam, "Investigating the Effect of Color Gamut Mapping Quantitatively and Visually" (2015). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Investigating the Effect of Color Gamut Mapping Quantitatively and Visually by Anupam Dhopade A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Print Media in the School of Media Sciences in the College of Imaging Arts and Sciences of the Rochester Institute of Technology May 2015 Primary Thesis Advisor: Professor Robert Chung Secondary Thesis Advisor: Professor Christine Heusner School of Media Sciences Rochester Institute of Technology Rochester, New York Certificate of Approval Investigating the Effect of Color Gamut Mapping Quantitatively and Visually This is to certify that the Master’s Thesis of Anupam Dhopade has been approved by the Thesis Committee as satisfactory for the thesis requirement for the Master of Science degree at the convocation of May 2015 Thesis Committee: __________________________________________ Primary Thesis Advisor, Professor Robert Chung __________________________________________ Secondary Thesis Advisor, Professor Christine Heusner __________________________________________ Graduate Director, Professor Christine Heusner __________________________________________ Administrative Chair, School of Media Sciences, Professor Twyla Cummings ACKNOWLEDGEMENT I take this opportunity to express my sincere gratitude and thank all those who have supported me throughout the MS course here at RIT. -
Fast and Stable Color Balancing for Images and Augmented Reality
Fast and Stable Color Balancing for Images and Augmented Reality Thomas Oskam 1,2 Alexander Hornung 1 Robert W. Sumner 1 Markus Gross 1,2 1 Disney Research Zurich 2 ETH Zurich Abstract This paper addresses the problem of globally balanc- ing colors between images. The input to our algorithm is a sparse set of desired color correspondences between a source and a target image. The global color space trans- formation problem is then solved by computing a smooth Source Image Target Image Color Balanced vector field in CIE Lab color space that maps the gamut of the source to that of the target. We employ normalized ra- dial basis functions for which we compute optimized shape parameters based on the input images, allowing for more faithful and flexible color matching compared to existing RBF-, regression- or histogram-based techniques. Further- more, we show how the basic per-image matching can be Rendered Objects efficiently and robustly extended to the temporal domain us- Tracked Colors balancing Augmented Image ing RANSAC-based correspondence classification. Besides Figure 1. Two applications of our color balancing algorithm. Top: interactive color balancing for images, these properties ren- an underexposed image is balanced using only three user selected der our method extremely useful for automatic, consistent correspondences to a target image. Bottom: our extension for embedding of synthetic graphics in video, as required by temporally stable color balancing enables seamless compositing applications such as augmented reality. in augmented reality applications by using known colors in the scene as constraints. 1. Introduction even for different scenes. With today’s tools this process re- quires considerable, cost-intensive manual efforts. -
Hiding Color Watermarks in Halftone Images Using Maximum-Similarity
Signal Processing: Image Communication 48 (2016) 1–11 Contents lists available at ScienceDirect Signal Processing: Image Communication journal homepage: www.elsevier.com/locate/image Hiding color watermarks in halftone images using maximum- similarity binary patterns Pedro Garcia Freitas a,n, Mylène C.Q. Farias b, Aletéia P.F. Araújo a a Department of Computer Science, University of Brasília (UnB), Brasília, Brazil b Department of Electrical Engineering, University of Brasília (UnB), Brasília, Brazil article info abstract Article history: This paper presents a halftoning-based watermarking method that enables the embedding of a color Received 3 June 2016 image into binary black-and-white images. To maintain the quality of halftone images, the method maps Received in revised form watermarks to halftone channels using homogeneous dot patterns. These patterns use a different binary 25 August 2016 texture arrangement to embed the watermark. To prevent a degradation of the host image, a max- Accepted 25 August 2016 imization problem is solved to reduce the associated noise. The objective function of this maximization Available online 26 August 2016 problem is the binary similarity measure between the original binary halftone and a set of randomly Keywords: generated patterns. This optimization problem needs to be solved for each dot pattern, resulting in Color embedding processing overhead and a long running time. To overcome this restriction, parallel computing techni- Halftone ques are used to decrease the processing time. More specifically, the method is tested using a CUDA- Color restoration based parallel implementation, running on GPUs. The proposed technique produces results with high Watermarking Enhancement visual quality and acceptable processing time. -
JPEG-HDR: a Backwards-Compatible, High Dynamic Range Extension to JPEG
JPEG-HDR: A Backwards-Compatible, High Dynamic Range Extension to JPEG Greg Ward Maryann Simmons BrightSide Technologies Walt Disney Feature Animation Abstract What we really need for HDR digital imaging is a compact The transition from traditional 24-bit RGB to high dynamic range representation that looks and displays like an output-referred (HDR) images is hindered by excessively large file formats with JPEG, but holds the extra information needed to enable it as a no backwards compatibility. In this paper, we demonstrate a scene-referred standard. The next generation of HDR cameras simple approach to HDR encoding that parallels the evolution of will then be able to write to this format without fear that the color television from its grayscale beginnings. A tone-mapped software on the receiving end won’t know what to do with it. version of each HDR original is accompanied by restorative Conventional image manipulation and display software will see information carried in a subband of a standard output-referred only the tone-mapped version of the image, gaining some benefit image. This subband contains a compressed ratio image, which from the HDR capture due to its better exposure. HDR-enabled when multiplied by the tone-mapped foreground, recovers the software will have full access to the original dynamic range HDR original. The tone-mapped image data is also compressed, recorded by the camera, permitting large exposure shifts and and the composite is delivered in a standard JPEG wrapper. To contrast manipulation during image editing in an extended color naïve software, the image looks like any other, and displays as a gamut. -
14. Color Mapping
14. Color Mapping Jacobs University Visualization and Computer Graphics Lab Recall: RGB color model Jacobs University Visualization and Computer Graphics Lab Data Analytics 691 CMY color model • The CMY color model is related to the RGB color model. •Itsbasecolorsare –cyan(C) –magenta(M) –yellow(Y) • They are arranged in a 3D Cartesian coordinate system. • The scheme is subtractive. Jacobs University Visualization and Computer Graphics Lab Data Analytics 692 Subtractive color scheme • CMY color model is subtractive, i.e., adding colors makes the resulting color darker. • Application: color printers. • As it only works perfectly in theory, typically a black cartridge is added in practice (CMYK color model). Jacobs University Visualization and Computer Graphics Lab Data Analytics 693 CMY color cube • All colors c that can be generated are represented by the unit cube in the 3D Cartesian coordinate system. magenta blue red black grey white cyan yellow green Jacobs University Visualization and Computer Graphics Lab Data Analytics 694 CMY color cube Jacobs University Visualization and Computer Graphics Lab Data Analytics 695 CMY color model Jacobs University Visualization and Computer Graphics Lab Data Analytics 696 CMYK color model Jacobs University Visualization and Computer Graphics Lab Data Analytics 697 Conversion • RGB -> CMY: • CMY -> RGB: Jacobs University Visualization and Computer Graphics Lab Data Analytics 698 Conversion • CMY -> CMYK: • CMYK -> CMY: Jacobs University Visualization and Computer Graphics Lab Data Analytics 699 HSV color model • While RGB and CMY color models have their application in hardware implementations, the HSV color model is based on properties of human perception. • Its application is for human interfaces. Jacobs University Visualization and Computer Graphics Lab Data Analytics 700 HSV color model The HSV color model also consists of 3 channels: • H: When perceiving a color, we perceive the dominant wavelength. -
GS9 Color Management
Ghostscript 9.21 Color Management Michael J. Vrhel, Ph.D. Artifex Software 7 Mt. Lassen Drive, A-134 San Rafael, CA 94903, USA www.artifex.com Abstract This document provides information about the color architecture in Ghostscript 9.21. The document is suitable for users who wish to obtain accurate color with their output device as well as for developers who wish to customize Ghostscript to achieve a higher level of control and/or interface with a different color management module. Revision 1.6 Artifex Software Inc. www.artifex.com 1 1 Introduction With release 9.0, the color architecture of Ghostscript was updated to primarily use the ICC[1] format for its color management needs. Prior to this release, Ghostscript's color architecture was based heavily upon PostScript[2] Color Management (PCM). This is due to the fact that Ghostscript was designed prior to the ICC format and likely even before there was much thought about digital color management. At that point in time, color management was very much an art with someone adjusting controls to achieve the proper output color. Today, almost all print color management is performed using ICC profiles as opposed to PCM. This fact along with the desire to create a faster, more flexible design was the motivation for the color architectural changes in release 9.0. Since 9.0, several new features and capabilities have been added. As of the 9.21 release, features of the color architecture include: • Easy to interface different CMMs (Color Management Modules) with Ghostscript. • ALL color spaces are defined in terms of ICC profiles. -
A Color Temperature-Based High-Speed Decolorization: an Empirical Approach for Tone Mapping Applications
1 A color temperature-based high-speed decolorization: an empirical approach for tone mapping applications Prasoon Ambalathankandy ID˙ , Yafei Ou ID˙ , and Masayuki Ikebe ID˙ Abstract—Grayscale images are fundamental to many image into global and local methods. Global methods can define processing applications like data compression, feature extraction, only one conversion function for all pixels, and most of printing and tone mapping. However, some image information these methods use all pixels in the image to determine the is lost when converting from color to grayscale. In this paper, we propose a light-weight and high-speed image decolorization function. On the other hand, local ones process the target method based on human perception of color temperatures. from neighboring pixels in the same way as a spatial filter, Chromatic aberration results from differential refraction of light the function is different for each pixel. However, both types depending on its wavelength. It causes some rays corresponding of methods face the issue of calculation cost, which comes to cooler colors (like blue, green) to converge before the warmer from optimization iterations or spatial filter processing. colors (like red, orange). This phenomena creates a perception of warm colors “advancing” toward the eye, while the cool colors We have developed a fast decolorization method that reflects to be “receding” away. In this proposed color to gray conversion the perception of warm and cool colors which is well known model, we implement a weighted blending function to combine in psychophysics studies [1]. Colors are arranged according to red (perceived warm) and blue (perceived cool) channel. -
Colormap : a Data-Driven Approach and Tool for Mapping Multivariate
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 24, NO. X, XXXXX 2018 1 ND 1 ColorMap : A Data-Driven Approach and Tool 2 for Mapping Multivariate Data to Color 3 Shenghui Cheng, Wei Xu, Member, IEEE, and Klaus Mueller, Senior Member, IEEE 4 Abstract—A wide variety of color schemes have been devised for mapping scalar data to color. We address the challenge of 5 color-mapping multivariate data. While a number of methods can map low-dimensional data to color, for example, using bilinear 6 or barycentric interpolation for two or three variables, these methods do not scale to higher data dimensions. Likewise, schemes that 7 take a more artistic approach through color mixing and the like also face limits when it comes to the number of variables they can 8 encode. Our approach does not have these limitations. It is data driven in that it determines a proper and consistent color map from first 9 embedding the data samples into a circular interactive multivariate color mapping display (ICD) and then fusing this display with a 10 convex (CIE HCL) color space. The variables (data attributes) are arranged in terms of their similarity and mapped to the ICD’s 11 boundary to control the embedding. Using this layout, the color of a multivariate data sample is then obtained via modified generalized 12 barycentric coordinate interpolation of the map. The system we devised has facilities for contrast and feature enhancement, supports 13 both regular and irregular grids, can deal with multi-field as well as multispectral data, and can produce heat maps, choropleth maps, 14 and diagrams such as scatterplots. -
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 OPTIMIZATION for REAL TIME APPLICATIONS By
TONE MAPPING OPTIMIZATION FOR REAL TIME APPLICATIONS by Siwei Zhao Submitted in partial fulfilment of the requirements for the degree of Master of Computer Science at Dalhousie University Halifax, Nova Scotia August 2019 © Copyright by Siwei Zhao, 2019 Table of Contents List of Tables .............................................................................................................................v List of Figures .......................................................................................................................... vi Abstract ................................................................................................................................. viii List of Abbreviations Used ....................................................................................................... ix Chapter 1 Introduction ..............................................................................................................1 1.1 Research Problems ......................................................................................................3 1.1.1 Objective Quality Evaluation for HDR Gaming Content ........................................3 1.1.2 Lookup Tables (LUTs) Interpolation In Video Games ............................................4 1.2 Objectives ...................................................................................................................5 1.3 Contributions ..............................................................................................................5 1.4 -
Approximate Cross Channel Color Mapping from Sparse Color Correspondences
2013 IEEE International Conference on Computer Vision Workshops Approximate Cross Channel Color Mapping from Sparse Color Correspondences Hasan Sheikh Faridul1,2, Jurgen Stauder1, Jonathan Kervec1, Alain Tremeau´ 2 1Technicolor Research & Innovation, France 2University of Saint Etienne, CNRS, UMR 5516, France {hasan.sheikh-faridul,jurgen.stauder}@technicolor.com [email protected] Abstract change (second step of color mapping), mostly channel- wise [2, 6, 9, 13, 27–31] color mapping models are used. We propose a color mapping method that compensates Channel-wise means that color mapping models are inde- color differences between images having a common seman- pendently estimated for each color channels (such as red, tic content such as multiple views of a scene taken from green and blue). In a channel-wise model, to estimate a different viewpoints. A so-called color mapping model is channel of one view, contribution is taken only from the usually estimated from color correspondences selected from corresponding channel of the other view, that is: those images. In this work, we introduce a color map- = ( ) ping that model color change in two steps: first, nonlin- Rview2 fR Rview1 ear, channel-wise mapping; second, linear, cross-channel Gview2 = fG(Gview1) (1) mapping. Additionally, unlike many state of the art meth- Bview2 = fB(Bview1). ods, we estimate the model from sparse matches and do not require dense geometric correspondences. We show that Channel-wise methods can be further categorized into linear well known cross-channel color change can be estimated [2, 28, 30, 31] or nonlinear [6, 9, 12, 14, 21] models. from sparse color correspondence.