Improving Image Quality in Multi-Channel Printing – Multilevel Halftoning, Color Separation and Graininess Characterization
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Color Management
Color Management hotoshop 5.0 was justifiably praised as a ground- breaking upgrade when it was released in the summer of 1998, although the changes made to the color P management setup were less well received in some quarters. This was because the revised system was perceived to be complex and unnecessary. Bruce Fraser once said of the Photoshop 5.0 color management system ‘it’s push-button simple, as long as you know which of the 60 or so buttons to push!’ Attitudes have changed since then (as has the interface) and it is fair to say that most people working today in the pre-press industry are now using ICC color profile managed workflows. The aim of this chapter is to introduce the basic concepts of color management before looking at the color management interface in Photoshop and the various color management settings. 1 Color management Adobe Photoshop CS6 for Photographers: www.photoshopforphotographers.com The need for color management An advertising agency art buyer was once invited to address a meeting of photographers. The chair, Mike Laye, suggested we could ask him anything we wanted, except ‘Would you like to see my book?’ And if he had already seen your book, we couldn’t ask him why he hadn’t called it back in again. And if he had called it in again we were not allowed to ask why we didn’t get the job. And finally, if we did get the job we were absolutely forbidden to ask why the color in the printed ad looked nothing like the original photograph! That in a nutshell is a problem which has bugged many of us throughout our working lives, and it is one which will be familiar to anyone who has ever experienced the difficulty of matching colors on a computer display with the original or a printed output. -
Pale Intrusions Into Blue: the Development of a Color Hannah Rose Mendoza
Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2004 Pale Intrusions into Blue: The Development of a Color Hannah Rose Mendoza Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected] THE FLORIDA STATE UNIVERSITY SCHOOL OF VISUAL ARTS AND DANCE PALE INTRUSIONS INTO BLUE: THE DEVELOPMENT OF A COLOR By HANNAH ROSE MENDOZA A Thesis submitted to the Department of Interior Design in partial fulfillment of the requirements for the degree of Master of Fine Arts Degree Awarded: Fall Semester, 2004 The members of the Committee approve the thesis of Hannah Rose Mendoza defended on October 21, 2004. _________________________ Lisa Waxman Professor Directing Thesis _________________________ Peter Munton Committee Member _________________________ Ricardo Navarro Committee Member Approved: ______________________________________ Eric Wiedegreen, Chair, Department of Interior Design ______________________________________ Sally Mcrorie, Dean, School of Visual Arts & Dance The Office of Graduate Studies has verified and approved the above named committee members. ii To Pepe, te amo y gracias. iii ACKNOWLEDGMENTS I want to express my gratitude to Lisa Waxman for her unflagging enthusiasm and sharp attention to detail. I also wish to thank the other members of my committee, Peter Munton and Rick Navarro for taking the time to read my thesis and offer a very helpful critique. I want to acknowledge the support received from my Mom and Dad, whose faith in me helped me get through this. Finally, I want to thank my son Jack, who despite being born as my thesis was nearing completion, saw fit to spit up on the manuscript only once. -
Color Gamut of Halftone Reproduction*
Color Gamut of Halftone Reproduction* Stefan Gustavson†‡ Department of Electrical Engineering, Linkøping University, S-581 83 Linkøping, Sweden Abstract tern then gets attenuated once more by the pattern of ink that resides on the surface, and the finally reflected light Color mixing by a halftoning process, as used for color is the result of these three effects combined: transmis- reproduction in graphic arts and most forms of digital sion through the ink film, diffused reflection from the hardcopy, is neither additive nor subtractive. Halftone substrate, and transmission through the ink film again. color reproduction with a given set of primary colors is The left-hand side of Fig. 2 shows an exploded view of heavily influenced not only by the colorimetric proper- the ink layer and the substrate, with the diffused reflected ties of the full-tone primaries, but also by effects such pattern shown on the substrate. The final viewed image as optical and physical dot gain and the halftone geom- is a view from the top of these two layers, as shown to etry. We demonstrate that such effects not only distort the right in Fig. 2. The dots do not really increase in the transfer characteristics of the process, but also have size, but they have a shadow around the edge that makes an impact on the size of the color gamut. In particular, a them appear larger, and the image is darker than what large dot gain, which is commonly regarded as an un- would have been the case without optical dot gain. wanted distortion, expands the color gamut quite con- siderably. -
Color Mixing Ratios
Colour Mixing: Ratios Color Theory with Tracy Moreau Learn more at DecoArt’s Art For Everyone Learning Center www.tracymoreau.net Primary Colours In painting, the three primary colours are yellow, red, and blue. These colors cannot be created by mixing other colours. They are called primary because all other colours are derived from them. Mixing Primary Colours Creates Secondary Colours If you combine two primary colours you get a secondary colour. For example, red and blue make violet, yellow and red make orange, and blue and yellow make green. If you mix all of the primary colours together you get black. The Mixing Ratio for Primary Colours To get orange, you mix the primary colours red and yellow. The mixing ratio of these two colours determines which shade of orange you will get after mixing. For example, if you use more red than yellow you will get a reddish-orange. If you add more yellow than red you will get a yellowish-orange. Experiment with the shades you have to see what you can create. Try out different combinations and mixing ratios and keep a written record of your results so that you can mix the colours again for future paintings. www.tracymoreau.net Tertiary Colours By mixing a primary and a secondary colour or two secondary colours you get a tertiary colour. Tertiary colours such as blue-lilac, yellow-green, green-blue, orange-yellow, red-orange, and violet-red are all created by combining a primary and a secondary colour. The Mixing Ratios of Light and Dark Colours If you want to darken a colour, you only need to add a small amount of black or another dark colour. -
Image Processing
IMAGE PROCESSING ROBOTICS CLUB SUMMER CAMP’12 WHAT IS IMAGE PROCESSING? IMAGE PROCESSING = IMAGE + PROCESSING WHAT IS IMAGE? IMAGE = Made up of PIXELS Each Pixels is like an array of Numbers. Numbers determine colour of Pixel. TYPES OF IMAGES 1. BINARY IMAGE 2. GREYSCALE IMAGE 3. COLOURED IMAGE BINARY IMAGE Each Pixel has either 1 (White) or 0 (Black) Depth =1 (bit) Number of Channels = 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 GRAYSCALE Each Pixel has a value from 0 to 255. 0 : black and 1 : White Between 0 and 255 are shades of b&w. Depth=8 (bits) Number of Channels =1 GRAYSCALE IMAGE RGB IMAGE Each Pixel stores 3 values :- R : 0- 255 G: 0 -255 B : 0-255 Depth=8 (bits) Number of Channels = 3 RGB IMAGE HSV IMAGE Each pixel stores 3 values :- H ( hue ) : 0 -180 S (saturation) : 0-255 V (value) : 0-255 Depth = 8 (bits) Number of Channels = 3 Note : Hue in general is from 0-360 , but as hue is 8 bits in OpenCV , it is shrinked to 180 STARTING WITH OPENCV OpenCV is a library for C language developed for Image Processing To embed opencv library in Dev C complier , follow instructions in :- http://opencv.willowgarage.com/wiki/DevCpp HEADER FILES IN C After embedding openCV library in Dev C include following header files:- #include "cv.h" #include "highgui.h" IMAGE POINTER An image is stored as a structure IplImage with following elements :- int height Width int width int nChannels int depth Height char *imageData int widthStep …. -
Preparing Images for Delivery
TECHNICAL PAPER Preparing Images for Delivery TABLE OF CONTENTS So, you’ve done a great job for your client. You’ve created a nice image that you both 2 How to prepare RGB files for CMYK agree meets the requirements of the layout. Now what do you do? You deliver it (so you 4 Soft proofing and gamut warning can bill it!). But, in this digital age, how you prepare an image for delivery can make or 13 Final image sizing break the final reproduction. Guess who will get the blame if the image’s reproduction is less than satisfactory? Do you even need to guess? 15 Image sharpening 19 Converting to CMYK What should photographers do to ensure that their images reproduce well in print? 21 What about providing RGB files? Take some precautions and learn the lingo so you can communicate, because a lack of crystal-clear communication is at the root of most every problem on press. 24 The proof 26 Marking your territory It should be no surprise that knowing what the client needs is a requirement of pro- 27 File formats for delivery fessional photographers. But does that mean a photographer in the digital age must become a prepress expert? Kind of—if only to know exactly what to supply your clients. 32 Check list for file delivery 32 Additional resources There are two perfectly legitimate approaches to the problem of supplying digital files for reproduction. One approach is to supply RGB files, and the other is to take responsibility for supplying CMYK files. Either approach is valid, each with positives and negatives. -
Color Mixing Challenge
COLOR MIXING CHALLENGE Target age group: any age Purpose of activity: to experiment with paint and discover color combinations that will make many different shades of the basic colors Materials needed: copies of the pattern page printed onto heavy card stock paper, small paint brushes, paper towels, paper plates to use as palettes (or half-sheets of card stock), a bowl of water to rinse brushes, acrylic paints in these colors: red, blue, yellow, and white (NOTE: Try to purchase the most “true” colors you can-- a royal blue, a true red, a medium yellow.) Time needed to complete activity: about 30 minutes (not including set-up and clean-up time) How to prepare: Copy (or print out) a pattern page for each student. Give each student a paper plate containing a marble-sized blob of red, blue, yellow and white. (Have a few spare plates available in case they run out of mixing space on their fi rst plate.) Also provide a paper towel and a bowl of rinse water. If a student runs out of a particular color of paint, give them a dab more. This will avoid wasting a lot of paint. (If you let the students fi ll their own paints, they will undoubtedly waste a lot of paint. In my experience, students almost always over-estimate how much paint they need.) What to do: It’s up to you (the adult in charge) how much instruction to give ahead of time. You may want to discuss color theory quite a bit, or you may want to emphasize the experimental nature of this activity and let the students discover color combinations for themselves. -
Computational RYB Color Model and Its Applications
IIEEJ Transactions on Image Electronics and Visual Computing Vol.5 No.2 (2017) -- Special Issue on Application-Based Image Processing Technologies -- Computational RYB Color Model and its Applications Junichi SUGITA† (Member), Tokiichiro TAKAHASHI†† (Member) †Tokyo Healthcare University, ††Tokyo Denki University/UEI Research <Summary> The red-yellow-blue (RYB) color model is a subtractive model based on pigment color mixing and is widely used in art education. In the RYB color model, red, yellow, and blue are defined as the primary colors. In this study, we apply this model to computers by formulating a conversion between the red-green-blue (RGB) and RYB color spaces. In addition, we present a class of compositing methods in the RYB color space. Moreover, we prescribe the appropriate uses of these compo- siting methods in different situations. By using RYB color compositing, paint-like compositing can be easily achieved. We also verified the effectiveness of our proposed method by using several experiments and demonstrated its application on the basis of RYB color compositing. Keywords: RYB, RGB, CMY(K), color model, color space, color compositing man perception system and computer displays, most com- 1. Introduction puter applications use the red-green-blue (RGB) color mod- Most people have had the experience of creating an arbi- el3); however, this model is not comprehensible for many trary color by mixing different color pigments on a palette or people who not trained in the RGB color model because of a canvas. The red-yellow-blue (RYB) color model proposed its use of additive color mixing. As shown in Fig. -
Switchable Primaries Using Shiftable Layers of Color Filter Arrays
Switchable Primaries Using Shiftable Layers of Color Filter Arrays Behzad Sajadi ∗ Kazuhiro Hiwadaz Atsuto Makix Ramesh Raskar{ Aditi Majumdery Toshiba Corporation Toshiba Research Europe Camera Culture Group University of California, Irvine Cambridge Laboratory MIT Media Lab RGB Camera Our Camera Ground Truth Our Camera CMY Camera RGB Camera 8.14 15.87 Dark Scene sRGB Image 17.57 21.49 ∆E Difference ∆E Bright Scene CMY Camera Our Camera (2.36, 9.26, 1.96) (8.12, 29.30, 4.93) (7.51, 22.78, 4.39) Figure 1: Left: The CMY mode of our camera provides a superior SNR over a RGB camera when capturing a dark scene (top) and the RGB mode provides superior SNR over CMY camera when capturing a lighted scene. To demonstrate this, each image is marked with its quantitative SNR on the top left. Right: The RGBCY mode of our camera provides better color fidelity than a RGB or CMY camera for colorful scene (top). The DE deviation in CIELAB space of each of these images from a ground truth (captured using SOC-730 hyperspectral camera) is encoded as grayscale images with error statistics (mean, maximum and standard deviation) provided at the bottom of each image. Note the close match between the image captured with our camera and the ground truth. Abstract ment of the primaries in the CFA) to provide an optimal solution. We present a camera with switchable primaries using shiftable lay- We investigate practical design options for shiftable layering of the ers of color filter arrays (CFAs). By layering a pair of CMY CFAs in CFAs. -
Primary Color | 23
BRAND Style GuiDe PriMary Color | 23 PRIMARY COLOR The primary color for Brandeis IBS is Brandeis IBS Blue, which is also the color of Brandeis University. Brandeis IBS Blue is BrandeiS iBS BLUE to be used as the prominent color in all communications. The PANTONE 294 C primary color is ideal for use in: CMYK 100 | 86 | 14 | 24 • Headlines • Large areas of text RGB 0 | 46 | 108 • Large background shapes HEX #002E6C Always use the designated color values for physical and digital Brandeis IBS communications. WEB HEX for use with white backgrounds #002E6C DO NOT use a tint of the primary color. Always use the primary color at 100% saturation. PANTONE color is used in physical applications whenever possible to reinforce the visual brand identity. CMYK designation is used for physical applications as an alternative to PANTONE (with the exception of any Microsoft Office documents, which use RGB). RGB values are used for any digital communications (excluding websites and e-communications), and all Microsoft Office documents (physical or digital). HEX values are used for any digital communications (excluding websites and e-communications). The value is an exact match to RGB. WEB HEX values are designated so websites and e-communica- tions can meet accessibility requirements. This compliance will ensure that people with disabilities can use Brandeis IBS online communications. For more about accessibility, visit http://www.brandeis.edu/acserv/disabilities/index.html. For examples of how the primary color should be applied across communications, please see pages 30-44. BRAND Style GuiDe SeCondary Color | 24 SeCondary Color The secondary color for Brandeis IBS is Brandeis IBS Teal, which is to be used strongly throughout Brandeis IBS com- BrandeiS iBS teal munications. -
Visualizing the Novel Clinton Mullins Connecticut College, [email protected]
Connecticut College Digital Commons @ Connecticut College Computer Science Honors Papers Computer Science Department 2013 Visualizing the Novel Clinton Mullins Connecticut College, [email protected] Follow this and additional works at: http://digitalcommons.conncoll.edu/comscihp Part of the Computer Sciences Commons Recommended Citation Mullins, Clinton, "Visualizing the Novel" (2013). Computer Science Honors Papers. 4. http://digitalcommons.conncoll.edu/comscihp/4 This Honors Paper is brought to you for free and open access by the Computer Science Department at Digital Commons @ Connecticut College. It has been accepted for inclusion in Computer Science Honors Papers by an authorized administrator of Digital Commons @ Connecticut College. For more information, please contact [email protected]. The views expressed in this paper are solely those of the author. Visualizing Novelthe kiss me please Thesis and code written by Clint Mullins with Professor Bridget Baird as the project's faculty advisor. 1. Data Visualization Discussion of data visualization. 2. Visualizing the Novel Introduction to our problem and execution overview. 3. Related Works Technologies and libraries used for the project. .1 Semantic Meaning .2 Parsing Text .3 Topic Modeling .4 Other Visualizations 4. Methods Specific algorithms and execution details. .1 Gunning FOG Index .2 Character Extraction .3 Character Shaping .4 Gender Detection .5 Related Word Extraction .6 Moments / Emotion Spectrum / DISCO 5. The Visual Our visual model from conception to completion. .1 Concept Process .2 Current Visual Model .3 Java2D .4 Generalizing the Visual Model 6. Results Judging output on known texts. .1 Text One – Eternally .2 Text Two – Love is Better the Second Time Around .3 How Successful is This? 7. -
PRIMARY-CONSISTENT SOFT-DECISION COLOR DEMOSAIC for DIGITAL CAMERAS (Patent Pending)
PRIMARY-CONSISTENT SOFT-DECISION COLOR DEMOSAIC FOR DIGITAL CAMERAS (Patent Pending) Xiaolin Wu and Ning Zhang Department of Electrical and Computer Engineering McMaster University Hamilton, Ontario L8S 4M2 [email protected] ABSTRACT Another drawback of the existing color demosaic algorithms is that they interpolate missing color components at a Bayer color mosaic sampling scheme is widely used in digital pixel independently of the color interpolations at neighboring cameras. Given the resolution of CCD sensor arrays, the image pixels. The interpolation decision is made on a hypothesis on quality of digital cameras using Bayer sampling mosaic largely the local gradient direction. But these algorithms do not validate depends on the performance of the color demosaic process. A the underlying hypothesis after the color interpolation is done. common and serious weakness shared by all existing color The verification of the hypothesis is difficult if the pixels are demosaic algorithms is an inconsistency of sample treated individually. To overcome this drawback we introduce a interpolations in different primary color components, which is new notion of soft-decision color demosaic. At each pixel, the culprit for the most objectionable color artifacts. To cure the instead of forcing a decision on the gradient with insufficient problem we propose a primary-consistent color demosaic information to guide the interpolation, we make multiple algorithm. The performance of this algorithm is further hypotheses and interpolate missing color components for each enhanced by a soft-decision sample interpolation scheme. of the hypotheses. Then we examine the interpolation results Experiments demonstrate that the proposed framework of under different hypotheses in a window of the pixel in question, primary-consistent soft-decision color demosaic can and choose the one whose underlying hypothesis agrees with the significantly improve the image quality of digital cameras.