Solution Set #2
|
|
- Avice Charlotte Scott
- 5 years ago
- Views:
Transcription
1 Solution Set #. For the sampling function shown, analyze to determine its characteristics, e.g., the associated Nyquist sampling frequency (if any), whether a function sampled with s [x; x] may be recovered from the samples, the corresponding interpolation function, etc. This function may be written as the difference of two comb functions with the same separation parameter equal to : +! X +! X s [x; x] [x n x] [x n x ] n + X n n h ³ x n i! X + n h³ x x i! n n h COMB x i COMB x h COMB x i x COMB h ³ x n i! n ³ x x! n
2 S [ξ; x] F {s [x; x]} COMB [ ξ] COMB [ ξ] exp [ πiξ] COMB [ ξ] ( exp [ πiξ]) +! X [ ξ k] ( cos [πξ]+isin [πξ]) ξ! ( cos [πξ]) + µ cos π! +! ( cos [πk]) + ³ k! ( ) + ³ k ( ) if k is odd 0 if k is even COMB ξ ξ ξ! i sin [πξ]! i sin π k! i sin [πk]! i 0 k This means that the spectrum of the input object function will be translated to be centered at halfinteger values of ξ: F{f [x] s [x; x]} F [ξ] S [ξ; x] F [ξ] COMB ξ F [ξ] k F ξ k In other words, the central frequency of each replica of the object spectrum will be placed at a halfinteger value of ξ. The Nyquist frequency remains the same, but the spectrum of the interpolation function must be offset: X +! (F [ξ] S [ξ; x]) H [ξ] F ξ k RECT ξ x ˆF [ξ] ((F [ξ] S [ξ; x]) H [ξ]) ξ +
3 . A square CCD sensor with linear dimension of 7mm and pixel count along each axis of 04 pixels is used in a camera with a lens of focal length f 35mmthat is focused on a flat scene at a distance of z 500 mm. The schematic of the imaging system is shown below. Assuming ray optics (no diffraction), determine the resolution of the camera in line pairs per mm (analogous to cycles per mm for nonsinusoidal signals). This problem is actually pretty easy if you know the basics of optical imaging. The image formed by a lens with focal length f of an object located at distance z will be located at a distance z from the lens that satisfies the equations: + z z f 500 mm 35 mm z z z f z f 500 mm 35 mm mm mm The magnification of the image is the ratio of the distances: M T z mm z 500 mm which means that the image is smaller than the object and upside down (which has no consequence). The fact that the image is smaller suggests that the action of the lens is a minification rather than a magnification. The linear dimension of the sensor with 04 pixels is 7mm, which means that the linear dimension of the pixel (assuming 00% fill factor) is: 7mm μm So the projected size of the pixel on the object is: 7mm μm 93 A line pair consists of two adjacent pixels (one each white and black), which has a period of 90.8 μm 8.64 μm 0.8 mm So the spatial resolution in line pairs per millimeter is: line pairs 0.8 mm line pairs 5.6 mm 3
4 3. A flat object with uniform reflectance with value ρ is illuminated by a light source with intensity distribution h i [x, y] 55 exp ³[x i x 0 ] +[y y 0 ] The resulting image is quantized to k bits of intensity resolution. Assume that the eye can detect an abrupt change of gray scale of eight shades of intensity over the dynamic range. Determine the value of k where false contouring is visible. The profile of the object along the x-axis is a Gaussian function: h i [x, 0] 55 exp ³[x i x 0 ] +[0 y 0 ] This is plotted for x 0 y 0 0: i[x,0] x So we want to ensure that i 8 56 k k 56 3 k 5 8 4
5 4. Sketch the -D image that would be obtained for the previous problem if k. If k, there are 4 gray values i 0,,, 3, and the result is obtained by evaluating the greatest integer of i [x, 0] 56 µ h ³ i 64 exp [x x 0 ] +[0 y 0 ] + i[x,0] x 5
6 5. High-definition TV generates images with a vertical resolution of 5 scan lines and a width to height aspect ratio of 6:9. The system transmits 8 bits of data for each of the three additive primary colors (red, green, blue). Determine the number of bits per second necessary to store an HDTV program assuming no compression. zzzz first, find the number of pixels in the image. The number of pixels in each row is: The number of pixels per frame therefore is: 5 000, 50, 000 and the number of bits per frame is the number of pixels multiplied by the number of bits per pixel: In US television, there are 30 frames per second, so the number of bits per second is: bits per second gigabytes per second The remaining missing piece of information is the length of the program in seconds; for a one-hour program, the number of bits is: bits per hour 679 gigabytes per hour o an uncompressed program will fill up your hard disk fairly fast, hence one reason to find useful video compression routines. 6
7 6. Use the program of your choice (Matlab, MathCAD, Excel, etc.) to do the following () construct and graph the following -D functions, () quantize to one bit by thresholding, and (3) quantize to one bit by error diffusion. h (a) f [n] cos π n i, 56 n 55 8 (a) f [n] before and after independent quantization to one bit (two levels); the graph of the thresholded function is scaled to have the same extrema as f [n]; (b)f [n] before and after error-diffused quantization to one bit; (c) detail view of (b), showing oscillations between the two output levels in the vicinity of the most rapid change in amplitude 7
8 h (b) f [n] cos π n i, 56 n 55 6 (a) f [n] before and after independent quantization to one bit (two levels); (b) magnified detail view of (a); (c) f [n] before and after error-diffused quantization to one bit; (d) detail view of (c), showing single oscillation between the two output levels near the most rapid change in amplitude. 8
Introduction. Prof. Lina Karam School of Electrical, Computer, & Energy Engineering Arizona State University
EEE 508 - Digital Image & Video Processing and Compression http://lina.faculty.asu.edu/eee508/ Introduction Prof. Lina Karam School of Electrical, Computer, & Energy Engineering Arizona State University
More informationExercise questions for Machine vision
Exercise questions for Machine vision This is a collection of exercise questions. These questions are all examination alike which means that similar questions may appear at the written exam. I ve divided
More informationOptical design of a high resolution vision lens
Optical design of a high resolution vision lens Paul Claassen, optical designer, paul.claassen@sioux.eu Marnix Tas, optical specialist, marnix.tas@sioux.eu Prof L.Beckmann, l.beckmann@hccnet.nl Summary:
More informationCS 548: Computer Vision REVIEW: Digital Image Basics. Spring 2016 Dr. Michael J. Reale
CS 548: Computer Vision REVIEW: Digital Image Basics Spring 2016 Dr. Michael J. Reale Human Vision System: Cones and Rods Two types of receptors in eye: Cones Brightness and color Photopic vision = bright-light
More informationThe Sine Function. Precalculus: Graphs of Sine and Cosine
Concepts: Graphs of Sine, Cosine, Sinusoids, Terminology (amplitude, period, phase shift, frequency). The Sine Function Domain: x R Range: y [ 1, 1] Continuity: continuous for all x Increasing-decreasing
More informationELEC Dr Reji Mathew Electrical Engineering UNSW
ELEC 4622 Dr Reji Mathew Electrical Engineering UNSW Filter Design Circularly symmetric 2-D low-pass filter Pass-band radial frequency: ω p Stop-band radial frequency: ω s 1 δ p Pass-band tolerances: δ
More informationLENSES. INEL 6088 Computer Vision
LENSES INEL 6088 Computer Vision Digital camera A digital camera replaces film with a sensor array Each cell in the array is a Charge Coupled Device light-sensitive diode that converts photons to electrons
More informationDECISION NUMBER FOURTEEN TO THE TREATY ON OPEN SKIES
DECISION NUMBER FOURTEEN TO THE TREATY ON OPEN SKIES OSCC.DEC 14 12 October 1994 METHODOLOGY FOR CALCULATING THE MINIMUM HEIGHT ABOVE GROUND LEVEL AT WHICH EACH VIDEO CAMERA WITH REAL TIME DISPLAY INSTALLED
More informationAmplitude, Reflection, and Period
SECTION 4.2 Amplitude, Reflection, and Period Copyright Cengage Learning. All rights reserved. Learning Objectives 1 2 3 4 Find the amplitude of a sine or cosine function. Find the period of a sine or
More informationCvision 2. António J. R. Neves João Paulo Silva Cunha. Bernardo Cunha. IEETA / Universidade de Aveiro
Cvision 2 Digital Imaging António J. R. Neves (an@ua.pt) & João Paulo Silva Cunha & Bernardo Cunha IEETA / Universidade de Aveiro Outline Image sensors Camera calibration Sampling and quantization Data
More informationImage and Video Processing
Image and Video Processing () Image Representation Dr. Miles Hansard miles.hansard@qmul.ac.uk Segmentation 2 Today s agenda Digital image representation Sampling Quantization Sub-sampling Pixel interpolation
More informationGeneral Imaging System
General Imaging System Lecture Slides ME 4060 Machine Vision and Vision-based Control Chapter 5 Image Sensing and Acquisition By Dr. Debao Zhou 1 2 Light, Color, and Electromagnetic Spectrum Penetrate
More informationOptical Components for Laser Applications. Günter Toesko - Laserseminar BLZ im Dezember
Günter Toesko - Laserseminar BLZ im Dezember 2009 1 Aberrations An optical aberration is a distortion in the image formed by an optical system compared to the original. It can arise for a number of reasons
More informationBias errors in PIV: the pixel locking effect revisited.
Bias errors in PIV: the pixel locking effect revisited. E.F.J. Overmars 1, N.G.W. Warncke, C. Poelma and J. Westerweel 1: Laboratory for Aero & Hydrodynamics, University of Technology, Delft, The Netherlands,
More information4-4 Graphing Sine and Cosine Functions
Describe how the graphs of f (x) and g(x) are related. Then find the amplitude of g(x), and sketch two periods of both functions on the same coordinate axes. 1. f (x) = sin x; g(x) = sin x The graph of
More informationE X P E R I M E N T 12
E X P E R I M E N T 12 Mirrors and Lenses Produced by the Physics Staff at Collin College Copyright Collin College Physics Department. All Rights Reserved. University Physics II, Exp 12: Mirrors and Lenses
More informationME 6406 MACHINE VISION. Georgia Institute of Technology
ME 6406 MACHINE VISION Georgia Institute of Technology Class Information Instructor Professor Kok-Meng Lee MARC 474 Office hours: Tues/Thurs 1:00-2:00 pm kokmeng.lee@me.gatech.edu (404)-894-7402 Class
More informationVariable microinspection system. system125
Variable microinspection system system125 Variable micro-inspection system Characteristics Large fields, high NA The variable microinspection system mag.x system125 stands out from conventional LD inspection
More informationIntroduction to DSP ECE-S352 Fall Quarter 2000 Matlab Project 1
Objective: Introduction to DSP ECE-S352 Fall Quarter 2000 Matlab Project 1 This Matlab Project is an extension of the basic correlation theory presented in the course. It shows a practical application
More information1 ONE- and TWO-DIMENSIONAL HARMONIC OSCIL- LATIONS
SIMG-232 LABORATORY #1 Writeup Due 3/23/2004 (T) 1 ONE- and TWO-DIMENSIONAL HARMONIC OSCIL- LATIONS 1.1 Rationale: This laboratory (really a virtual lab based on computer software) introduces the concepts
More informationLecture Notes 10 Image Sensor Optics. Imaging optics. Pixel optics. Microlens
Lecture Notes 10 Image Sensor Optics Imaging optics Space-invariant model Space-varying model Pixel optics Transmission Vignetting Microlens EE 392B: Image Sensor Optics 10-1 Image Sensor Optics Microlens
More informationPHYS 160 Astronomy. When analyzing light s behavior in a mirror or lens, it is helpful to use a technique called ray tracing.
Optics Introduction In this lab, we will be exploring several properties of light including diffraction, reflection, geometric optics, and interference. There are two sections to this lab and they may
More informationEvaluating Commercial Scanners for Astronomical Images. The underlying technology of the scanners: Pixel sizes:
Evaluating Commercial Scanners for Astronomical Images Robert J. Simcoe Associate Harvard College Observatory rjsimcoe@cfa.harvard.edu Introduction: Many organizations have expressed interest in using
More information8.2 IMAGE PROCESSING VERSUS IMAGE ANALYSIS Image processing: The collection of routines and
8.1 INTRODUCTION In this chapter, we will study and discuss some fundamental techniques for image processing and image analysis, with a few examples of routines developed for certain purposes. 8.2 IMAGE
More informationIntegral 3-D Television Using a 2000-Scanning Line Video System
Integral 3-D Television Using a 2000-Scanning Line Video System We have developed an integral three-dimensional (3-D) television that uses a 2000-scanning line video system. An integral 3-D television
More informationDigital Imaging with the Nikon D1X and D100 cameras. A tutorial with Simon Stafford
Digital Imaging with the Nikon D1X and D100 cameras A tutorial with Simon Stafford Contents Fundamental issues of Digital Imaging Camera controls Practical Issues Questions & Answers (hopefully!) Digital
More informationDigital Imaging Rochester Institute of Technology
Digital Imaging 1999 Rochester Institute of Technology So Far... camera AgX film processing image AgX photographic film captures image formed by the optical elements (lens). Unfortunately, the processing
More informationImage and Multidimensional Signal Processing
Image and Multidimensional Signal Processing Professor William Hoff Dept of Electrical Engineering &Computer Science http://inside.mines.edu/~whoff/ Digital Image Fundamentals 2 Digital Image Fundamentals
More information1 Laboratory 7: Fourier Optics
1051-455-20073 Physical Optics 1 Laboratory 7: Fourier Optics 1.1 Theory: References: Introduction to Optics Pedrottis Chapters 11 and 21 Optics E. Hecht Chapters 10 and 11 The Fourier transform is an
More informationChapter 2: Digital Image Fundamentals. Digital image processing is based on. Mathematical and probabilistic models Human intuition and analysis
Chapter 2: Digital Image Fundamentals Digital image processing is based on Mathematical and probabilistic models Human intuition and analysis 2.1 Visual Perception How images are formed in the eye? Eye
More informationYou analyzed graphs of functions. (Lesson 1-5)
You analyzed graphs of functions. (Lesson 1-5) LEQ: How do we graph transformations of the sine and cosine functions & use sinusoidal functions to solve problems? sinusoid amplitude frequency phase shift
More informationCameras. CSE 455, Winter 2010 January 25, 2010
Cameras CSE 455, Winter 2010 January 25, 2010 Announcements New Lecturer! Neel Joshi, Ph.D. Post-Doctoral Researcher Microsoft Research neel@cs Project 1b (seam carving) was due on Friday the 22 nd Project
More informationECEN 4606, UNDERGRADUATE OPTICS LAB
ECEN 4606, UNDERGRADUATE OPTICS LAB Lab 3: Imaging 2 the Microscope Original Version: Professor McLeod SUMMARY: In this lab you will become familiar with the use of one or more lenses to create highly
More informationGraphing Sine and Cosine
The problem with average monthly temperatures on the preview worksheet is an example of a periodic function. Periodic functions are defined on p.254 Periodic functions repeat themselves each period. The
More informationSECTION I - CHAPTER 2 DIGITAL IMAGING PROCESSING CONCEPTS
RADT 3463 - COMPUTERIZED IMAGING Section I: Chapter 2 RADT 3463 Computerized Imaging 1 SECTION I - CHAPTER 2 DIGITAL IMAGING PROCESSING CONCEPTS RADT 3463 COMPUTERIZED IMAGING Section I: Chapter 2 RADT
More informationDigital Images & Image Quality
Introduction to Medical Engineering (Medical Imaging) Suetens 1 Digital Images & Image Quality Ho Kyung Kim Pusan National University Radiation imaging DR & CT: x-ray Nuclear medicine: gamma-ray Ultrasound
More informationAcquisition and representation of images
Acquisition and representation of images Stefano Ferrari Università degli Studi di Milano stefano.ferrari@unimi.it Methods for mage Processing academic year 2017 2018 Electromagnetic radiation λ = c ν
More informationBe aware that there is no universal notation for the various quantities.
Fourier Optics v2.4 Ray tracing is limited in its ability to describe optics because it ignores the wave properties of light. Diffraction is needed to explain image spatial resolution and contrast and
More informationAcquisition and representation of images
Acquisition and representation of images Stefano Ferrari Università degli Studi di Milano stefano.ferrari@unimi.it Elaborazione delle immagini (Image processing I) academic year 2011 2012 Electromagnetic
More informationEE119 Introduction to Optical Engineering Spring 2003 Final Exam. Name:
EE119 Introduction to Optical Engineering Spring 2003 Final Exam Name: SID: CLOSED BOOK. THREE 8 1/2 X 11 SHEETS OF NOTES, AND SCIENTIFIC POCKET CALCULATOR PERMITTED. TIME ALLOTTED: 180 MINUTES Fundamental
More informationPhysics 3340 Spring Fourier Optics
Physics 3340 Spring 011 Purpose Fourier Optics In this experiment we will show how the Fraunhofer diffraction pattern or spatial Fourier transform of an object can be observed within an optical system.
More informationMTF and PSF measurements of the CCD detector for the Euclid visible channel
MTF and PSF measurements of the CCD273-84 detector for the Euclid visible channel I. Swindells* a, R. Wheeler a, S. Darby a, S. Bowring a, D. Burt a, R. Bell a, L. Duvet b, D. Walton c, R. Cole c a e2v
More informationSupplementary Figure 1. Effect of the spacer thickness on the resonance properties of the gold and silver metasurface layers.
Supplementary Figure 1. Effect of the spacer thickness on the resonance properties of the gold and silver metasurface layers. Finite-difference time-domain calculations of the optical transmittance through
More informationThis experiment is under development and thus we appreciate any and all comments as we design an interesting and achievable set of goals.
Experiment 7 Geometrical Optics You will be introduced to ray optics and image formation in this experiment. We will use the optical rail, lenses, and the camera body to quantify image formation and magnification;
More informationFourier transforms, SIM
Fourier transforms, SIM Last class More STED Minflux Fourier transforms This class More FTs 2D FTs SIM 1 Intensity.5 -.5 FT -1.5 1 1.5 2 2.5 3 3.5 4 4.5 5 6 Time (s) IFT 4 2 5 1 15 Frequency (Hz) ff tt
More informationImage Formation. Light from distant things. Geometrical optics. Pinhole camera. Chapter 36
Light from distant things Chapter 36 We learn about a distant thing from the light it generates or redirects. The lenses in our eyes create images of objects our brains can process. This chapter concerns
More informationIntroduction to Computer Vision
Introduction to Computer Vision CS / ECE 181B Thursday, April 1, 2004 Course Details HW #0 and HW #1 are available. Course web site http://www.ece.ucsb.edu/~manj/cs181b Syllabus, schedule, lecture notes,
More informationOptics Practice. Version #: 0. Name: Date: 07/01/2010
Optics Practice Date: 07/01/2010 Version #: 0 Name: 1. Which of the following diagrams show a real image? a) b) c) d) e) i, ii, iii, and iv i and ii i and iv ii and iv ii, iii and iv 2. A real image is
More informationVision. The eye. Image formation. Eye defects & corrective lenses. Visual acuity. Colour vision. Lecture 3.5
Lecture 3.5 Vision The eye Image formation Eye defects & corrective lenses Visual acuity Colour vision Vision http://www.wired.com/wiredscience/2009/04/schizoillusion/ Perception of light--- eye-brain
More informationA 3D Multi-Aperture Image Sensor Architecture
A 3D Multi-Aperture Image Sensor Architecture Keith Fife, Abbas El Gamal and H.-S. Philip Wong Department of Electrical Engineering Stanford University Outline Multi-Aperture system overview Sensor architecture
More informationFRAUNHOFER AND FRESNEL DIFFRACTION IN ONE DIMENSION
FRAUNHOFER AND FRESNEL DIFFRACTION IN ONE DIMENSION Revised November 15, 2017 INTRODUCTION The simplest and most commonly described examples of diffraction and interference from two-dimensional apertures
More informationSPECKLE INTERFEROMETRY WITH TEMPORAL PHASE EVALUATION: INFLUENCE OF DECORRELATION, SPECKLE SIZE, AND NON-LINEARITY OF THE CAMERA
SPECKLE INTERFEROMETRY WITH TEMPORAL PHASE EVALUATION: INFLUENCE OF DECORRELATION, SPECKLE SIZE, AND NON-LINEARITY OF THE CAMERA C. Joenathan*, P. Haible, B. Franze, and H. J. Tiziani Universitaet Stuttgart,
More informationImage Acquisition Hardware. Image Acquisition and Representation. CCD Camera. Camera. how digital images are produced
Image Acquisition Hardware Image Acquisition and Representation how digital images are produced how digital images are represented photometric models-basic radiometry image noises and noise suppression
More informationDetectionofMicrostrctureofRoughnessbyOpticalMethod
Global Journal of Researches in Engineering Chemical Engineering Volume 1 Issue Version 1.0 Year 01 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA)
More informationSharpness, Resolution and Interpolation
Sharpness, Resolution and Interpolation Introduction There are a lot of misconceptions about resolution, camera pixel count, interpolation and their effect on astronomical images. Some of the confusion
More informationLab Report 3: Speckle Interferometry LIN PEI-YING, BAIG JOVERIA
Lab Report 3: Speckle Interferometry LIN PEI-YING, BAIG JOVERIA Abstract: Speckle interferometry (SI) has become a complete technique over the past couple of years and is widely used in many branches of
More informationIMAGE SENSOR SOLUTIONS. KAC-96-1/5" Lens Kit. KODAK KAC-96-1/5" Lens Kit. for use with the KODAK CMOS Image Sensors. November 2004 Revision 2
KODAK for use with the KODAK CMOS Image Sensors November 2004 Revision 2 1.1 Introduction Choosing the right lens is a critical aspect of designing an imaging system. Typically the trade off between image
More informationA Study of Slanted-Edge MTF Stability and Repeatability
A Study of Slanted-Edge MTF Stability and Repeatability Jackson K.M. Roland Imatest LLC, 2995 Wilderness Place Suite 103, Boulder, CO, USA ABSTRACT The slanted-edge method of measuring the spatial frequency
More informationSection 7.6 Graphs of the Sine and Cosine Functions
4 Section 7. Graphs of the Sine and Cosine Functions In this section, we will look at the graphs of the sine and cosine function. The input values will be the angle in radians so we will be using x is
More informationImage Acquisition and Representation. Camera. CCD Camera. Image Acquisition Hardware
Image Acquisition and Representation Camera Slide 1 how digital images are produced how digital images are represented Slide 3 First photograph was due to Niepce of France in 1827. Basic abstraction is
More informationImage Acquisition and Representation
Image Acquisition and Representation how digital images are produced how digital images are represented photometric models-basic radiometry image noises and noise suppression methods 1 Image Acquisition
More informationDIGITAL IMAGE PROCESSING (COM-3371) Week 2 - January 14, 2002
DIGITAL IMAGE PROCESSING (COM-3371) Week 2 - January 14, 22 Topics: Human eye Visual phenomena Simple image model Image enhancement Point processes Histogram Lookup tables Contrast compression and stretching
More informationHigh-speed Micro-crack Detection of Solar Wafers with Variable Thickness
High-speed Micro-crack Detection of Solar Wafers with Variable Thickness T. W. Teo, Z. Mahdavipour, M. Z. Abdullah School of Electrical and Electronic Engineering Engineering Campus Universiti Sains Malaysia
More informationEE 392B: Course Introduction
EE 392B Course Introduction About EE392B Goals Topics Schedule Prerequisites Course Overview Digital Imaging System Image Sensor Architectures Nonidealities and Performance Measures Color Imaging Recent
More information5.3 Trigonometric Graphs. Copyright Cengage Learning. All rights reserved.
5.3 Trigonometric Graphs Copyright Cengage Learning. All rights reserved. Objectives Graphs of Sine and Cosine Graphs of Transformations of Sine and Cosine Using Graphing Devices to Graph Trigonometric
More informationCPSC 4040/6040 Computer Graphics Images. Joshua Levine
CPSC 4040/6040 Computer Graphics Images Joshua Levine levinej@clemson.edu Lecture 04 Displays and Optics Sept. 1, 2015 Slide Credits: Kenny A. Hunt Don House Torsten Möller Hanspeter Pfister Agenda Open
More informationDETERMINING CALIBRATION PARAMETERS FOR A HARTMANN- SHACK WAVEFRONT SENSOR
DETERMINING CALIBRATION PARAMETERS FOR A HARTMANN- SHACK WAVEFRONT SENSOR Felipe Tayer Amaral¹, Luciana P. Salles 2 and Davies William de Lima Monteiro 3,2 Graduate Program in Electrical Engineering -
More informationModule 3: Video Sampling Lecture 18: Filtering operations in Camera and display devices. The Lecture Contains: Effect of Temporal Aperture:
The Lecture Contains: Effect of Temporal Aperture: Spatial Aperture: Effect of Display Aperture: file:///d /...e%20(ganesh%20rana)/my%20course_ganesh%20rana/prof.%20sumana%20gupta/final%20dvsp/lecture18/18_1.htm[12/30/2015
More information30 lesions. 30 lesions. false positive fraction
Solutions to the exercises. 1.1 In a patient study for a new test for multiple sclerosis (MS), thirty-two of the one hundred patients studied actually have MS. For the data given below, complete the two-by-two
More informationSupplementary Figure 1. GO thin film thickness characterization. The thickness of the prepared GO thin
Supplementary Figure 1. GO thin film thickness characterization. The thickness of the prepared GO thin film is characterized by using an optical profiler (Bruker ContourGT InMotion). Inset: 3D optical
More informationDesign Description Document
UNIVERSITY OF ROCHESTER Design Description Document Flat Output Backlit Strobe Dare Bodington, Changchen Chen, Nick Cirucci Customer: Engineers: Advisor committee: Sydor Instruments Dare Bodington, Changchen
More informationOFFSET AND NOISE COMPENSATION
OFFSET AND NOISE COMPENSATION AO 10V 8.1 Offset and fixed pattern noise reduction Offset variation - shading AO 10V 8.2 Row Noise AO 10V 8.3 Offset compensation Global offset calibration Dark level is
More informationProblems from the 3 rd edition
(2.1-1) Find the energies of the signals: a) sin t, 0 t π b) sin t, 0 t π c) 2 sin t, 0 t π d) sin (t-2π), 2π t 4π Problems from the 3 rd edition Comment on the effect on energy of sign change, time shifting
More informationPhysicsAndMathsTutor.com 1
PhysicsAndMathsTutor.com 1 Q1. Just over two hundred years ago Thomas Young demonstrated the interference of light by illuminating two closely spaced narrow slits with light from a single light source.
More informationLaser Telemetric System (Metrology)
Laser Telemetric System (Metrology) Laser telemetric system is a non-contact gauge that measures with a collimated laser beam (Refer Fig. 10.26). It measure at the rate of 150 scans per second. It basically
More informationChapter 4 MASK Encryption: Results with Image Analysis
95 Chapter 4 MASK Encryption: Results with Image Analysis This chapter discusses the tests conducted and analysis made on MASK encryption, with gray scale and colour images. Statistical analysis including
More informationFiber Optic Communications
Fiber Optic Communications ( Chapter 2: Optics Review ) presented by Prof. Kwang-Chun Ho 1 Section 2.4: Numerical Aperture Consider an optical receiver: where the diameter of photodetector surface area
More informationComputer Vision. Howie Choset Introduction to Robotics
Computer Vision Howie Choset http://www.cs.cmu.edu.edu/~choset Introduction to Robotics http://generalrobotics.org What is vision? What is computer vision? Edge Detection Edge Detection Interest points
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY. 2.71/2.710 Optics Spring 14 Practice Problems Posted May 11, 2014
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 2.71/2.710 Optics Spring 14 Practice Problems Posted May 11, 2014 1. (Pedrotti 13-21) A glass plate is sprayed with uniform opaque particles. When a distant point
More informationCopyright 2009 Pearson Education, Inc. Slide Section 8.2 and 8.3-1
8.3-1 Transformation of sine and cosine functions Sections 8.2 and 8.3 Revisit: Page 142; chapter 4 Section 8.2 and 8.3 Graphs of Transformed Sine and Cosine Functions Graph transformations of y = sin
More informationEC-433 Digital Image Processing
EC-433 Digital Image Processing Lecture 2 Digital Image Fundamentals Dr. Arslan Shaukat 1 Fundamental Steps in DIP Image Acquisition An image is captured by a sensor (such as a monochrome or color TV camera)
More informationLight gathering Power: Magnification with eyepiece:
Telescopes Light gathering Power: The amount of light that can be gathered by a telescope in a given amount of time: t 1 /t 2 = (D 2 /D 1 ) 2 The larger the diameter the smaller the amount of time. If
More information1. The ray diagram shows the position and size of the image, I, of an object, O, formed by a lens, L.
Medical applications of physics 1. The ray diagram shows the position and size of the image, I, of an object, O, formed by a lens, L. L O P I (a) What type of lens is shown in the ray diagram? Name the
More informationUnit 1: Image Formation
Unit 1: Image Formation 1. Geometry 2. Optics 3. Photometry 4. Sensor Readings Szeliski 2.1-2.3 & 6.3.5 1 Physical parameters of image formation Geometric Type of projection Camera pose Optical Sensor
More informationAcquisition Basics. How can we measure material properties? Goal of this Section. Special Purpose Tools. General Purpose Tools
Course 10 Realistic Materials in Computer Graphics Acquisition Basics MPI Informatik (moving to the University of Washington Goal of this Section practical, hands-on description of acquisition basics general
More informationSOME PHYSICAL LAYER ISSUES. Lecture Notes 2A
SOME PHYSICAL LAYER ISSUES Lecture Notes 2A Delays in networks Propagation time or propagation delay, t prop Time required for a signal or waveform to propagate (or move) from one point to another point.
More informationExercise Problems: Information Theory and Coding
Exercise Problems: Information Theory and Coding Exercise 9 1. An error-correcting Hamming code uses a 7 bit block size in order to guarantee the detection, and hence the correction, of any single bit
More informationPLazeR. a planar laser rangefinder. Robert Ying (ry2242) Derek Xingzhou He (xh2187) Peiqian Li (pl2521) Minh Trang Nguyen (mnn2108)
PLazeR a planar laser rangefinder Robert Ying (ry2242) Derek Xingzhou He (xh2187) Peiqian Li (pl2521) Minh Trang Nguyen (mnn2108) Overview & Motivation Detecting the distance between a sensor and objects
More informationAberrations of a lens
Aberrations of a lens 1. What are aberrations? A lens made of a uniform glass with spherical surfaces cannot form perfect images. Spherical aberration is a prominent image defect for a point source on
More informationName: Period: Date: Math Lab: Explore Transformations of Trig Functions
Name: Period: Date: Math Lab: Explore Transformations of Trig Functions EXPLORE VERTICAL DISPLACEMENT 1] Graph 2] Explain what happens to the parent graph when a constant is added to the sine function.
More informationEvaluation of laser-based active thermography for the inspection of optoelectronic devices
More info about this article: http://www.ndt.net/?id=15849 Evaluation of laser-based active thermography for the inspection of optoelectronic devices by E. Kollorz, M. Boehnel, S. Mohr, W. Holub, U. Hassler
More informationOverview. Pinhole camera model Projective geometry Vanishing points and lines Projection matrix Cameras with Lenses Color Digital image
Camera & Color Overview Pinhole camera model Projective geometry Vanishing points and lines Projection matrix Cameras with Lenses Color Digital image Book: Hartley 6.1, Szeliski 2.1.5, 2.2, 2.3 The trip
More informationGaussian Ray Tracing Technique
Gaussian Ray Tracing Technique Positive Lenses. A positive lens has two focal points one on each side of the lens; both are at the same focal distance f from the lens. Parallel rays of light coming from
More informationDetermination of Focal Length of A Converging Lens and Mirror
Physics 41 Determination of Focal Length of A Converging Lens and Mirror Objective: Apply the thin-lens equation and the mirror equation to determine the focal length of a converging (biconvex) lens and
More informationPrecalculus ~ Review Sheet
Period: Date: Precalculus ~ Review Sheet 4.4-4.5 Multiple Choice 1. The screen below shows the graph of a sound recorded on an oscilloscope. What is the period and the amplitude? (Each unit on the t-axis
More informationOptical Coherence: Recreation of the Experiment of Thompson and Wolf
Optical Coherence: Recreation of the Experiment of Thompson and Wolf David Collins Senior project Department of Physics, California Polytechnic State University San Luis Obispo June 2010 Abstract The purpose
More informationNoise Characteristics of a High Dynamic Range Camera with Four-Chip Optical System
Journal of Electrical Engineering 6 (2018) 61-69 doi: 10.17265/2328-2223/2018.02.001 D DAVID PUBLISHING Noise Characteristics of a High Dynamic Range Camera with Four-Chip Optical System Takayuki YAMASHITA
More informationProjection. Announcements. Müller-Lyer Illusion. Image formation. Readings Nalwa 2.1
Announcements Mailing list (you should have received messages) Project 1 additional test sequences online Projection Readings Nalwa 2.1 Müller-Lyer Illusion Image formation object film by Pravin Bhat http://www.michaelbach.de/ot/sze_muelue/index.html
More informationSpatial harmonic distortion: a test for focal plane nonlinearity
Spatial harmonic distortion: a test for focal plane nonlinearity Glenn D. Boreman, MEMBER SPIE Anthony B. James University of Central Florida Electrical Engineering Department Center for Research in Electro-Optics
More informationPhotons and solid state detection
Photons and solid state detection Photons represent discrete packets ( quanta ) of optical energy Energy is hc/! (h: Planck s constant, c: speed of light,! : wavelength) For solid state detection, photons
More information