Http://www.euhou.net http://www.euhou.net.

Slides:



Advertisements
Similar presentations
Pixels and Digital Images Yrd. Doc. Dr. Ahmet Sayar Kocaeli Universitesi Bilgisayar Muhendisligi Ileri Bilgisayar Grafikleri.
Advertisements

Detecting and Mixing Colors STEM DIGITAL Institute Rob Snyder.
Copyright 2006 by Pearson Education 1 Building Java Programs Supplement 3G: Graphics.
SalsaJ tutorial.
CSE Lecture 6 – Complex Numbers & Images
DIGITAL IMAGE PROCESSING CMSC 150: Lecture 14. Conventional Cameras  Entirely chemical and mechanical processes  Film: records a chemical record of.
© red ©
CS430 © 2006 Ray S. Babcock CS430 – Image Processing Image Representation.
CSc 461/561 CSc 461/561 Multimedia Systems Part A: 2. Image.
1 Internet Graphics. 2 Representing Images  Raster Image: Images consist of “dots” of color, not lines  Pixel: Picture element-tiny rectangle  Resolution:
Digital Colour Theory. What is colour theory? It is the theory behind colour mixing and colour combination.
Colour Digital Multimedia, 2nd edition Nigel Chapman & Jenny Chapman
Digital Multimedia, 2nd edition Nigel Chapman & Jenny Chapman Chapter 6 This presentation © 2004, MacAvon Media Productions Colour.
Fundamentals of Photoshop
Image processing Second lecture. Image Image Representation We have seen that the human visual system (HVS) receives an input image as a collection of.
ELEMENTS OF ART Building Blocks.
CMYK vs. RGB Design. Primary colors The colors that make up the base for every other color created. Depending on whether you are looking at it from science,
Quiz Review - Drawing Kickback - line type most specific to designers that is drawn with an emphasis at the beginning and at the end. Feathering - a vague-looking.
Welcome Topic: Pixels A.M.Meshkatur Rahman Class: vii Roll: 07.
Digital Images Chapter 8, Exploring the Digital Domain.
Color. -Visual light -An integral part of the sculpture -Creates desired effect -Distinguish items -Strengthen interest.
TOPIC 4 INTRODUCTION TO MEDIA COMPUTATION: DIGITAL PICTURES Notes adapted from Introduction to Computing and Programming with Java: A Multimedia Approach.
Objective Understand concepts used to create digital graphics. Course Weight : 15% Part Three : Concepts of Digital Graphics.
I-1 Steps of Image Generation –Create a model of the objects –Create a model for the illumination of the objects –Create an image (render) the result I.
Foundations of Web Design I Photoshop CS5 Michael Daniel
25.2 The human eye The eye is the sensory organ used for vision.
Images The Science of Images What is an Image on the computer? The Psychology of Images What do we use images for? What effect color has on our mood and.
Web Colors. Web Colors: Up until now, we have been using only pre- defined color names, such as "orange" and "lightblue". As web designers, we need the.
Photoshop I I450 Technology Seminar. Adobe Photoshop Illustrator Acrobat InDesign ImageReady.
Color and Resolution Introduction to Digital Imaging.
CSC Computing with Images
Registration to the program for pilot middle/high schools: Beta version to be discussed for database Teachers concerned (team): Name1/Firstname1: Resource.
Image Representation. Digital Cameras Scanned Film & Photographs Digitized TV Signals Computer Graphics Radar & Sonar Medical Imaging Devices (X-Ray,
Chapter 16 Light and Color  16.1 Properties and Sources of Light  16.2 Color and Vision  16.3 Photons and Atoms.
Homework Assignment You are going to research any artist of your choosing from any time period or genre. You are going to complete a one page double- spaced.
# Red Green Blue Digital Color RGB to HEX.
Computer Vision Introduction to Digital Images.
Ch 6 Color Image processing CS446 Instructor: Nada ALZaben.
DIGITAL IMAGE. Basic Image Concepts An image is a spatial representation of an object An image can be thought of as a function with resulting values of.
CS 111 – Sept. 3 More data representation Review hex notation Text –ASCII and Unicode Sound and images Commitment: –For Wednesday: Please read pp
Digital Image Processing In The Name Of God Digital Image Processing Lecture6: Color Image Processing M. Ghelich Oghli By: M. Ghelich Oghli
The Seven Elements of Art Ms. Hanson/ART 1. Definition of The Elements of Art The elements of art are a commonly used group of aspects of a work of art.
Digital Imaging Fundamentals Ms. Hema C.R. School of Mechatronic Engineering.
` Tracking the Eyes using a Webcam Presented by: Kwesi Ackon Kwesi Ackon Supervisor: Mr. J. Connan.
Color Web Design Professor Frank. Color Displays Based on cathode ray tubes (CRTs) or back- lighted flat-screen Monitors transmit light - displays use.
Computer Science and Software Engineering© 2014 Project Lead The Way, Inc. Bits and Bytes.
CS 101 – Sept. 14 Review Huffman code Image representation –B/W and color schemes –File size issues.
June 14, ‘99 COLORS IN MATLAB.
Intro to Color Theory. Objectives Identify and discuss various color models including RGB, CMYK, Black/white and spot color. Investigate color mixing.
ISAN-DSP GROUP Digital Image Fundamentals ISAN-DSP GROUP What is Digital Image Processing ? Processing of a multidimensional pictures by a digital computer.
HSB to RGB to HEX.
TOPIC 4 INTRODUCTION TO MEDIA COMPUTATION: DIGITAL PICTURES Notes adapted from Introduction to Computing and Programming with Java: A Multimedia Approach.
1 HTML. 2 Full forms WWW – world Wide Web HTTP – Hyper Text Transfer Protocol HTML – Hyper Text Markup Language.
Digital Image: Rendering of a continuously varying scene with a finite array of picture elements, where each one has a discrete intensity or color 39.
An Introduction to Digital Image Processing Dr.Amnach Khawne Department of Computer Engineering, KMITL.
Lesson 13 – Color and Typography. 2 Objectives Understand basic color theory. Understand the color wheel. Understand how color is presented on a computer.
Image: Susanne Rafelski, Marshall lab Introduction to Digital Image Analysis Part I: Digital Images Kurt Thorn NIC UCSF.
Introduction to Digital Image Analysis Kurt Thorn NIC.
The Elements of Art Mrs. Love The Elements of Art There are 7 basic elements of art. These elements are the visual language of art.
SalsaJ (Such a Lovely Software for Astronomy) Practical Session.
Sampling, Quantization, Color Models & Indexed Color
Images In Matlab.
How to Convert Pictures into Numbers
Images Presentation Name Course Name Unit # – Lesson #.# – Lesson Name
Two ways to discuss color 1) Addition 2) Subtraction
Images Presentation Name Course Name Unit # – Lesson #.# – Lesson Name
Colors Computers build colors from Red, Green, and Blue; not Red, Blue, and Yellow. RGB = Red Green Blue Creating Colors Red + Blue = Purple No Red, No.
What Color is it?.
Digital Image Processing
Basic Concepts of Digital Imaging
Presentation transcript:

http://www.euhou.net http://www.euhou.net

SalsaJ

Didactical software for image and data handling Pedagogical resources : SalsaJ software Didactical software for image and data handling Such A Lovely Software for Astronomy, in Java Multi-platform (Windows, Linux, Mac) Java, modularity; easily extensible to implement new fonctionnalities Adaptation in different languages; recently in arabic; chinese in progress Free of charge (download from the EU-HOU web site); open-source Up to date sources (derived from the free medical research tool ImageJ developed at NIH); adapted to astronomy (FITS format; photometry…); friendly tool for classrooms Developed by F-HOU ; SalsaJ v2.0 to be released by the end of 2007

SalsaJ: a multilingual interface

Digital Images

Digital Images

Digital Images A digital image is a set of values gathered in a 2D (or 3D) array Each element is a pixel (picture element) Each pixel has a corresponding physical size Each pixel can have one or more values 1 value = “black&white” images 3 values = true-color RGB images

Digital Images Black and white images are actually gray-level images Each pixel has one value corresponding to a particular shade of gray 0 for black and max for white max depends on the dynamics of the image 8-bits : 255 16-bits : 65 535 32-bits : real values

Digital Images Example : Black : (0,0,0) White : (255,255,255) Red : (255,0,0) Green : (0,255,0) Blue : (0,0,255) Cyan : (0,255,255) Magenta : (255,0,255) Yellow : (255,255,0) Orange : (255,190,93) Gray : (128,128,128)

SalsaJ Open

SalsaJ Brightness/Contrast

Measurements In pixels

Scale

In km

doublet du sodium

SalsaJ Pixel size=1500/(80-7)=20.54m/pixel Crater size ~ (177-52)x20.54~2567.5m Image obtained with Mars Global Surveyor (NASA/JPL/Malin Space Sciences Systems)

SalsaJ Stellar objects = point sources Convolved by the Point Spread Function (PSF) of the « instrument » (atmosphere + optics) PSF ~ bell-like shape function ~ Gaussian + tails Characterised by its Full Width Half Maximum (FWHM) in arcsec (cf pixel size) Good sampling: FWHM ~2-3 pixel size 1/2 FWHM 1/2

SalsaJ : photometry Use: Fstar= Sum of intensity (pixels with r<r1) –Sky*N1 N1 = Number of pixels in the radius r1 Sky = Sum of intensity (pixels with r2<r <r3) / N23 N23 = Number of pixels in the corona r2 < r < r3 r3 Use: Instrumental value proportional to the stellar object flux (luminosity) r1 r2

SalsaJ

SalsaJ Cepheids in the SMC distances

SalsaJ Perspectives: Addition of other astronomical functionalities (astrometry, PSF photometry, etc.) Optimisation of the tool with intensive testing in schools Extension to biological imaging and developments of more synergy with ImageJ (sustainability of the software). Translation in other languages