HW 2 Discussion Remember, everything is still an illusion.

Slides:



Advertisements
Similar presentations
CS Spring 2009 CS 414 – Multimedia Systems Design Lecture 4 – Digital Image Representation Klara Nahrstedt Spring 2009.
Advertisements

Embedded Image Processing on FPGA Brian Kinsella Supervised by Dr Fearghal Morgan.
Grey Level Enhancement Contrast stretching Linear mapping Non-linear mapping Efficient implementation of mapping algorithms Design of classes to support.
Image Processing Tutorial
6. Gray level enhancement Some of the simplest, yet most useful, image processing operations involve the adjustment of brightness, contrast or colour in.
Image Processing. Processing Digital Images digital images are often processed using “digital filters” digital filters are based on mathematical functions.
1Ellen L. Walker ImageJ Java image processing tool from NIH Reads / writes a large variety of images Many image processing operations.
CS324e - Elements of Graphics and Visualization Color Histograms.
Face Recognition and Biometric Systems 2005/2006 Filters.
The Distance Scale Ladder A Nested Chain of Cumulative Uncertainty.
6/9/2015Digital Image Processing1. 2 Example Histogram.
Multimedia Data Introduction to Image Processing Dr Mike Spann Electronic, Electrical and Computer.
IMAGE 1 An image is a two dimensional Function f(x,y) where x and y are spatial coordinates And f at any x,y is related to the brightness at that point.
Introduction to Image Analysis Presented to Microscopy and Microscopy Education 11 March 2000 New Orleans, LA.
So you Want to use Motic Images Plus Dazzle your students! Impress that special someone! Earn millions!
…….CT Physics - Continued V.G.WimalasenaPrincipal School of radiography.
Spectral contrast enhancement
The Digital Image.
1. What is dynamic range? 2. If one camera “captures a smaller dynamic range” than another camera, and they both took a picture of the same scene, how.
CS654: Digital Image Analysis Lecture 17: Image Enhancement.
The Digital Image Dr. John Ryan.
CCD Detectors CCD=“charge coupled device” Readout method:
Image Processing Image Histogram Lecture
Calibration & Measurements. Calibrating the System Before we can make any measurements we need to calibrate our imaging system to create real world numbers.
When the photowell is full, a white value occurs. No photons after this are recorded, so all detail for these pixels are lost. If the electron count.
Multimedia Data Introduction to Image Processing Dr Sandra I. Woolley Electronic, Electrical.
Digital Image Processing Lecture 4: Image Enhancement: Point Processing Prof. Charlene Tsai.
AdeptSight Image Processing Tools Lee Haney January 21, 2010.
MULTIMEDIA TECHNOLOGY SMM 3001 MEDIA - IMAGES. Processing digital Images digital images are often processed using “digital filters” digital images are.
Resolution = the number of photosites (pixels) in the array of your sensor or the total number of buckets Bit Depth / Pixel Depth.
7 elements of remote sensing process 1.Energy Source (A) 2.Radiation & Atmosphere (B) 3.Interaction with Targets (C) 4.Recording of Energy by Sensor (D)
Lecture 3 The Digital Image – Part I - Single Channel Data 12 September
Pachon Sky Camera Christopher Stubbs Chuck Claver Jan 25, 2014.
Digital Image Processing Part 1 Introduction. The eye.
MULTIMEDIA INPUT / OUTPUT TECHNOLOGIES
Measuring Sky Brightness with a Digital Camera Paris 2004.
11/29/ Image Processing. 11/29/ Systems and Software Image file formats Image processing applications.
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.
Autonomous Robots Vision © Manfred Huber 2014.
Image Processing and Analysis I Materials extracted from Gonzalez & Wood and Castleman.
Intelligent Vision Systems ENT 496 Image Filtering and Enhancement Hema C.R. Lecture 4.
Last updated Heejune Ahn, SeoulTech
Homework 2 (Due: 3/26) A. Given a grayscale image I,
CH2. Point Processes Arithmetic Operation Histogram Equalization
Digital Image Processing Part 2 Contrast processing.
Digital Image Processing
CS Spring 2010 CS 414 – Multimedia Systems Design Lecture 4 – Audio and Digital Image Representation Klara Nahrstedt Spring 2010.
Image Enhancement in Spatial Domain Presented by : - Mr. Trushar Shah. ME/MC Department, U.V.Patel College of Engineering, Kherva.
Machine Vision Edge Detection Techniques ENT 273 Lecture 6 Hema C.R.
Digital Image Processing Lecture 4: Image Enhancement: Point Processing January 13, 2004 Prof. Charlene Tsai.
Digital Image Processing Image Enhancement in Spatial Domain
July 25th, 2000WFC3 Critical Science Review1 Performance Summary in Key Science Areas Verify that WFC3 as designed is capable of carrying out the WFC3.
In conclusion the intensity level of the CCD is linear up to the saturation limit, but there is a spilling of charges well before the saturation if.
Introduction to Digital Image Analysis Kurt Thorn NIC.
SalsaJ (Such a Lovely Software for Astronomy) Practical Session.
HADI Tutorial HADI Usage Contents 1.System Requirements 2.Capture Image 3.Calibration 4.Properties of Measurement Tools 5.View and Display 6.Show.
CCD Calibrations Eliminating noise and other sources of error.
Stellar Distances SL/HL – Option E.3.
Discussion #29 – Images II
Chapter 8, Exploring the Digital Domain
Histogram Probability distribution of the different grays in an image.
Pulsar 3: Significant peaks, well above the noise
Resolution Resolution: 6 x 4.
Presentation 4 Zach Robertson.
Grey Level Enhancement
Modern Observational/Instrumentation Techniques Astronomy 500
Intensity Transformations and Spatial Filtering
Intensity Transform Contrast Stretching Y ← u0+γ*(Y-u)/s
CS 101 – Nov. 18 Finish image enhancement Communication (Chapter 15)
Image segmentation Grey scale image Binary image
Presentation transcript:

HW 2 Discussion Remember, everything is still an illusion

Stars.txt and Galaxy.txt First thing to do is to understand the structure of the two files. THEY ARE NOT THE SAME Stars.txt is the same as moon.txt Galaxy.txt is in a slightly different 2D format:

Read Original.txt file in python

Find the Stars This is about finding local maxima in a 2D array tion-in-a-2d-array tion-in-a-2d-array detection-in-a-noisy-2d-array detection-in-a-noisy-2d-array 88-fast-2d-peak-finder 88-fast-2d-peak-finder finding/ finding/

What does the data actually look like in the Array? USE MEDIAN FILTERING TO FIND THE LOCAL PEAKS BECAUSE ITS VALUE IS MUCH HIGHER THAN MEDIAN – OR USE RANKS. THE POINT IS THAT MAXIMUM IN THIS DATA ARE DEFINED BY A SINGLE PIXEL VALUE AND NOT A REGION (UNLESS THE STARS ARE SATURATED ON THE DETECTOR IN WHICH CASE THEY ARE JUNK DATA

You have to think a bit about the data as well Its easy to find too many “stars” in this data file:

Real Stars + Defects – need physically sensible threshold - experiment

Contrast Adjusting – not all those faint things might be stars ….

Bubble Chart – what “problem” does this indicate?

What the galaxy should look like in sensible lookup table

Luminosity Profile

Calibration errors?

Histogram – Just Work with Raw Data – 105 million Pixels What does this distribution tell you about your gray scale dynamic range?

Histogram Equalization Stretch (how many pixels go into what bit ranges)

Make the Galaxy Disappear

Low Surface Brightness Galaxies Galaxies are extended objects imaged against the noise of the night sky