Color Management Guide
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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. -
CDOT Shaded Color and Grayscale Printing Reference File Management
CDOT Shaded Color and Grayscale Printing This document guides you through the set-up and printing process for shaded color and grayscale Sheet Files. This workflow may be used any time the user wants to highlight specific areas for things such as phasing plans, public meetings, ROW exhibits, etc. Please note that the use of raster images (jpg, bmp, tif, ets.) will dramatically increase the processing time during printing. Reference File Management Adjustments must be made to some of the reference file settings in order to achieve the desired print quality. The settings that need to be changed are the Slot Numbers and the Update Sequence. Slot Numbers are unique identifiers assigned to reference files and can be called out individually or in groups within a pen table for special processing during printing. The Update Sequence determines the order in which files are refreshed on the screen and printed on paper. Reference file Slot Number Categories: 0 = Sheet File (black)(this is the active dgn file.) 1-99 = Proposed Primary Discipline (Black) 100-199 = Existing Topo (light gray) 200-299 = Proposed Other Discipline (dark gray) 300-399 = Color Shaded Areas Note: All data placed in the Sheet File will be printed black. Items to be printed in color should be in their own file. Create a new file using the standard CDOT seed files and reference design elements to create color areas. If printing to a black and white printer all colors will be printed grayscale. Files can still be printed using the default printer drivers and pen tables, however shaded areas will lose their transparency and may print black depending on their level. -
The Art of Digital Black & White by Jeff Schewe There's Just Something
The Art of Digital Black & White By Jeff Schewe There’s just something magical about watching an image develop on a piece of photo paper in the developer tray…to see the paper go from being just a blank white piece of paper to becoming a photograph is what many photographers think of when they think of Black & White photography. That process of watching the image develop is what got me hooked on photography over 30 years ago and Black & White is where my heart really lives even though I’ve done more color work professionally. I used to have the brown stains on my fingers like any good darkroom tech, but commercially, I turned toward color photography. Later, when going digital, I basically gave up being able to ever achieve what used to be commonplace from the darkroom–until just recently. At about the same time Kodak announced it was going to stop making Black & White photo paper, Epson announced their new line of digital ink jet printers and a new ink, Ultrachrome K3 (3 Blacks- hence the K3), that has given me hope of returning to darkroom quality prints but with a digital printer instead of working in a smelly darkroom environment. Combine the new printers with the power of digital image processing in Adobe Photoshop and the capabilities of recent digital cameras and I think you’ll see a strong trend towards photographers going digital to get the best Black & White prints possible. Making the optimal Black & White print digitally is not simply a click of the shutter and push button printing. -
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. -
Grayscale Lithography Creating Complex 2.5D Structures in Thick Photoresist by Direct Laser Writing
EPIC Meeting on Wafer Level Optics Grayscale Lithography Creating complex 2.5D structures in thick photoresist by direct laser writing 07/11/2019 Dominique Collé - Grayscale Lithography Heidelberg Instruments in a Nutshell • A world leader in the production of innovative, high- precision maskless aligners and laser lithography systems • Extensive know-how in developing customized photolithography solutions • Providing customer support throughout system’s lifetime • Focus on high quality, high fidelity, high speed, and high precision • More than 200 employees worldwide (and growing fast) • 40 million Euros turnover in 2017 • Founded in 1984 • An installation base of over 800 systems in more than 50 countries • 35 years of experience 07/11/2019 Dominique Collé - Grayscale Lithography Principle of Grayscale Photolithography UV exposure with spatially modulated light intensity After development: the intensity gradient has been transferred into resist topography. Positive photoresist Substrate Afterward, the resist topography can be transfered to a different material: the substrate itself (etching) or a molding material (electroforming, OrmoStamp®). 07/11/2019 Dominique Collé - Grayscale Lithography Applications Microlens arrays Fresnel lenses Diffractive Optical elements • Wavefront sensor • Reduced lens volume • Modified phase profile • Fiber coupling • Mobile devices • Split & shape beam • Light homogenization • Miniature cameras • Complex light patterns 07/11/2019 Dominique Collé - Grayscale Lithography Applications Diffusers & reflectors -
Color Printing Techniques
4-H Photography Skill Guide Color Printing Techniques Enlarging Color Negatives Making your own color prints from Color Relations color negatives provides a whole new area of Before going ahead into this fascinating photography for you to enjoy. You can make subject of color printing, let’s make sure we prints nearly any size you want, from small ones understand some basic photographic color and to big enlargements. You can crop pictures for the visual relationships. composition that’s most pleasing to you. You can 1. White light (sunlight or the light from an control the lightness or darkness of the print, as enlarger lamp) is made up of three primary well as the color balance, and you can experiment colors: red, green, and blue. These colors are with control techniques to achieve just the effect known as additive primary colors. When you’re looking for. The possibilities for creating added together in approximately equal beautiful color prints are as great as your own amounts, they produce white light. imagination. You can print color negatives on conventional 2. Color‑negative film has a separate light‑ color printing paper. It’s the kind of paper your sensitive layer to correspond with each photofinisher uses. It requires precise processing of these three additive primary colors. in two or three chemical solutions and several Images recorded on these layers appear as washes in water. It can be processed in trays or a complementary (opposite) colors. drum processor. • A red subject records on the red‑sensitive layer as cyan (blue‑green). • A green subject records on the green‑ sensitive layer as magenta (blue‑red). -
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. -
Simplest Color Balance
Published in Image Processing On Line on 2011{10{24. Submitted on 2011{00{00, accepted on 2011{00{00. ISSN 2105{1232 c 2011 IPOL & the authors CC{BY{NC{SA This article is available online with supplementary materials, software, datasets and online demo at http://dx.doi.org/10.5201/ipol.2011.llmps-scb 2014/07/01 v0.5 IPOL article class Simplest Color Balance Nicolas Limare1, Jose-Luis Lisani2, Jean-Michel Morel1, Ana Bel´enPetro2, Catalina Sbert2 1 CMLA, ENS Cachan, France ([email protected], [email protected]) 2 TAMI, Universitat Illes Balears, Spain (fjoseluis.lisani, anabelen.petro, [email protected]) Abstract In this paper we present the simplest possible color balance algorithm. The assumption under- lying this algorithm is that the highest values of R, G, B observed in the image must correspond to white, and the lowest values to obscurity. The algorithm simply stretches, as much as it can, the values of the three channels Red, Green, Blue (R, G, B), so that they occupy the maximal possible range [0, 255] by applying an affine transform ax+b to each channel. Since many images contain a few aberrant pixels that already occupy the 0 and 255 values, the proposed method saturates a small percentage of the pixels with the highest values to 255 and a small percentage of the pixels with the lowest values to 0, before applying the affine transform. Source Code The source code (ANSI C), its documentation, and the online demo are accessible at the IPOL web page of this article1. -
Grayscale Vs. Monochrome Scanning
13615 NE 126th Place #450 Kirkland, WA 98034 USA Website:www.pimage.com Grayscale vs. Monochrome Scanning This document is intended to discuss why it is so important to scan microfilm and microfiche in grayscale and to show the limitations of monochrome scanning. The best analogy for the limitations of monochrome scanning is if you have every tried to photocopy your driver licenses. The picture can go completely black. This is because the copier can only reproduce full black or full white and not gray levels. If you place the copier in photo mode it is able to reproduce shades of gray. Grayscale scanning is analogous to the photo modes setting on your copier. The types of items on microfilm that are difficult to reproduce in monochrome are pencil on a blue form, light signatures, date stamps and embossing. In grayscale these items have a much higher probability to reproduce in the scanned version. Certainly there are instances where filming errors exist and the film is almost pure black or pure white. This can happen if the door to the room was opened during filming, if the canister had light intrusion prior to developing or if the chemicals or temperature were off on the developer. If these are identified the vendor can make a lamp adjustment in these sections of film or if they are frequent and the vendor has the proper cameras, they can scan at a higher bit depth. We have the ability to scan at bit depths higher than 8 bit gray up to 12 bits. 8 bit supports 256 levels of gray, 10bit supports 1024 levels and 12 bit 4096 levels. -
Basics of Color Management
Application Notes Basics of Color Management Basics of Color Management ErgoSoft AG Moosgrabenstr. 13 CH-8595 Altnau, Switzerland © 2010 ErgoSoft AG, All rights reserved. The information contained in this manual is based on information available at the time of publication and is sub- ject to change without notice. Accuracy and completeness are not warranted or guaranteed. No part of this manual may be reproduced or transmitted in any form or by any means, including electronic me- dium or machine-readable form, without the expressed written permission of ErgoSoft AG. Brand or product names are trademarks of their respective holders. The ErgoSoft RIP is available in different editions. Therefore the description of available features in this document does not necessarily reflect the license details of your edition of the ErgoSoft RIP. For information on the features included in your edition of the ErgoSoft RIPs refer to the ErgoSoft homepage or contact your dealer. Rev. 1.1 Basics of Color Management i Contents Introduction ................................................................................................................................................................. 1 Color Spaces ................................................................................................................................................................ 1 Basics ........................................................................................................................................................................ 1 CMYK ....................................................................................................................................................................... -
Scanning & Halftones
SCANNING & HALFTONES Ethics It is strongly recommend that you observe the rights of the original artist or publisher of the images you scan. If you plan to use a previously published image, contact the artist or publisher for information on obtaining permission. Scanning an Image Scanning converts a continuous tone image into a bitmap. Original photographic prints and photographic transparencies (slides) are continuous tone. The scanning process captures picture data as pixels. Think of a pixel as one tile in a mosaic. Bitmapped images Three primary pieces of information are relevant to all bitmapped images. 1. Dimensions Example: 2" x 2" 2. Color Mode Example: 256 level grayscale scan 3. Resolution Example: 300 ppi Basic Steps of Scanning 1. Place image on scanner bed Scanning & Halftones 2. Preview the image – click Preview 3. Select area to be scanned – drag a selection rectangle 4. Determine scan resolution (dpi or ppi) 5. Determine mode or pixel depth (grayscale, color, line art) 6. Scale selected area to desired dimensions (% of original) 7. Scan Resolution Resolution is the amount of something. something amount amount over physical distance fabric the number of stitches in fabric the number of stitches per inch in a needlepoint film the amount of grain in film the number of grains in a micro meter in film digital image the number of pixels the number of pixels per inch in a digital image Resolution is a unit of measure: Input Resolution the number of pixels per inch (ppi) of a scanned image or an image captured with a digital camera On Screen Resolution the number of pixels per inch displayed on your computer monitor (ppi or dpi) Output Resolution the number of dots per inch (dpi) printed by the printer (laser printer, ink jet printer, imagesetter) dpi or ppi refer to square pixels per inch of a bitmap file. -
Deep Learning-Based Color Holographic Microscopy
Deep learning-based color holographic microscopy Tairan Liu1,2,3†, Zhensong Wei1†, Yair Rivenson1,2,3†,*, Kevin de Haan1,2,3, Yibo Zhang1,2,3, Yichen Wu1,2,3, and Aydogan Ozcan1,2,3,4,* † Equally contributing authors * Corresponding authors: [email protected] ; [email protected] 1Electrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA. 2Bioengineering Department, University of California, Los Angeles, CA, 90095, USA. 3California NanoSystems Institute (CNSI), University of California, Los Angeles, CA, 90095, USA. 4Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. Abstract We report a framework based on a generative adversarial network (GAN) that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths. The trained network learns to eliminate missing-phase-related arti- facts, and generates an accurate color transformation for the reconstructed image. Our framework is ex- perimentally demonstrated using lung and prostate tissue sections that are labeled with different histo- logical stains. This framework is envisaged to be applicable to point-of-care histopathology, and pre- sents a significant improvement in the throughput of coherent microscopy systems given that only a sin- gle hologram of the specimen is required for accurate color imaging. 1. INTRODUCTION Histological staining of fixed, thin tissue sections mounted on glass slides is one of the fundamental steps required for the diagnoses of various medical conditions. Histological stains are used to highlight the constituent tissue parts by enhancing the colorimetric contrast of cells and subcellular components for microscopic inspection.