Introduction to Medical Imaging. Lecture 4: Fourier Theory = = ( ) 2sin(2 ) Introduction

Similar documents
Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation.

Introduction to the Fourier transform. Computer Vision & Digital Image Processing. The Fourier transform (continued) The Fourier transform (continued)

10. The Discrete-Time Fourier Transform (DTFT)

Lecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac.

A Propagating Wave Packet Group Velocity Dispersion

COMPUTER GENERATED HOLOGRAMS Optical Sciences 627 W.J. Dallas (Monday, April 04, 2005, 8:35 AM) PART I: CHAPTER TWO COMB MATH.

Chapter 6. The Discrete Fourier Transform and The Fast Fourier Transform

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.

[ ] [ ] DFT: Discrete Fourier Transform ( ) ( ) ( ) ( ) Congruence (Integer modulo m) N-point signal

2. Background Material

EE140 Introduction to Communication Systems Lecture 2

EEO 401 Digital Signal Processing Prof. Mark Fowler

DISCRETE TIME FOURIER TRANSFORM (DTFT)

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS

Title: Vibrational structure of electronic transition

Problem Set #2 Due: Friday April 20, 2018 at 5 PM.

Linear-Phase FIR Transfer Functions. Functions. Functions. Functions. Functions. Functions. Let

SECTION where P (cos θ, sin θ) and Q(cos θ, sin θ) are polynomials in cos θ and sin θ, provided Q is never equal to zero.

Where k is either given or determined from the data and c is an arbitrary constant.

Math 34A. Final Review

Lecture 37 (Schrödinger Equation) Physics Spring 2018 Douglas Fields

EECE 301 Signals & Systems Prof. Mark Fowler

2F1120 Spektrala transformer för Media Solutions to Steiglitz, Chapter 1

1 1 1 p q p q. 2ln x x. in simplest form. in simplest form in terms of x and h.

2. Finite Impulse Response Filters (FIR)

As the matrix of operator B is Hermitian so its eigenvalues must be real. It only remains to diagonalize the minor M 11 of matrix B.

Search sequence databases 3 10/25/2016

On the Hamiltonian of a Multi-Electron Atom

The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function

ECE Department Univ. of Maryland, College Park

ANALYSIS IN THE FREQUENCY DOMAIN

The Matrix Exponential

Higher order derivatives

Image Filtering: Noise Removal, Sharpening, Deblurring. Yao Wang Polytechnic University, Brooklyn, NY11201

High Energy Physics. Lecture 5 The Passage of Particles through Matter

LECTURE 5 Guassian Wave Packet

The Matrix Exponential

Topic 5: Discrete-Time Fourier Transform (DTFT)

Einstein Equations for Tetrad Fields

Sundials and Linear Algebra

Random Process Part 1

11: Echo formation and spatial encoding

Deift/Zhou Steepest descent, Part I

1973 AP Calculus AB: Section I

orbiting electron turns out to be wrong even though it Unfortunately, the classical visualization of the

Addition of angular momentum

Addition of angular momentum

( ) = ( ) ( ) ( ) ( ) τ τ. This is a more complete version of the solutions for assignment 2 courtesy of the course TA

Types of Transfer Functions. Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters

[1] (20 points) Find the general solutions of y y 2y = sin(t) + e t. Solution: y(t) = y c (t) + y p (t). Complementary Solutions: y

1 General boundary conditions in diffusion

Section 11.6: Directional Derivatives and the Gradient Vector

6. The Interaction of Light and Matter

Optics and Non-Linear Optics I Non-linear Optics Tutorial Sheet November 2007

The graph of y = x (or y = ) consists of two branches, As x 0, y + ; as x 0, y +. x = 0 is the

ECE507 - Plasma Physics and Applications

Phys 402: Nonlinear Spectroscopy: SHG and Raman Scattering

de/dx Effectively all charged particles except electrons

Background: We have discussed the PIB, HO, and the energy of the RR model. In this chapter, the H-atom, and atomic orbitals.

There is an arbitrary overall complex phase that could be added to A, but since this makes no difference we set it to zero and choose A real.

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA

Thomas Whitham Sixth Form

Coupled Pendulums. Two normal modes.

EEO 401 Digital Signal Processing Prof. Mark Fowler

Difference -Analytical Method of The One-Dimensional Convection-Diffusion Equation

Mathematics. Complex Number rectangular form. Quadratic equation. Quadratic equation. Complex number Functions: sinusoids. Differentiation Integration

Symmetric centrosymmetric matrix vector multiplication

Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters. Ideal Filters

NARAYANA I I T / P M T A C A D E M Y. C o m m o n P r a c t i c e T e s t 1 6 XII STD BATCHES [CF] Date: PHYSIS HEMISTRY MTHEMTIS

Bifurcation Theory. , a stationary point, depends on the value of α. At certain values

Procdings of IC-IDC0 ( and (, ( ( and (, and (f ( and (, rspctivly. If two input signals ar compltly qual, phas spctra of two signals ar qual. That is

Derivation of Electron-Electron Interaction Terms in the Multi-Electron Hamiltonian


Lecture 19: Free Energies in Modern Computational Statistical Thermodynamics: WHAM and Related Methods

Determination of Vibrational and Electronic Parameters From an Electronic Spectrum of I 2 and a Birge-Sponer Plot

Introduction to Condensed Matter Physics

Computing and Communications -- Network Coding

Function Spaces. a x 3. (Letting x = 1 =)) a(0) + b + c (1) = 0. Row reducing the matrix. b 1. e 4 3. e 9. >: (x = 1 =)) a(0) + b + c (1) = 0

dy 1. If fx ( ) is continuous at x = 3, then 13. If y x ) for x 0, then f (g(x)) = g (f (x)) when x = a. ½ b. ½ c. 1 b. 4x a. 3 b. 3 c.

Things I Should Know Before I Get to Calculus Class

Title. Author(s)Pei, Soo-Chang; Ding, Jian-Jiun. Issue Date Doc URL. Type. Note. File Information. Citationand Conference:

Integration by Parts

u 3 = u 3 (x 1, x 2, x 3 )

Announce. ECE 2026 Summer LECTURE OBJECTIVES READING. LECTURE #3 Complex View of Sinusoids May 21, Complex Number Review

Ch. 24 Molecular Reaction Dynamics 1. Collision Theory

Differential Equations

a 1and x is any real number.

u r du = ur+1 r + 1 du = ln u + C u sin u du = cos u + C cos u du = sin u + C sec u tan u du = sec u + C e u du = e u + C

ABEL TYPE THEOREMS FOR THE WAVELET TRANSFORM THROUGH THE QUASIASYMPTOTIC BOUNDEDNESS

Math 102. Rumbos Spring Solutions to Assignment #8. Solution: The matrix, A, corresponding to the system in (1) is

On the irreducibility of some polynomials in two variables

Chapter 5. Introduction. Introduction. Introduction. Finite Element Modelling. Finite Element Modelling

u x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula

y = 2xe x + x 2 e x at (0, 3). solution: Since y is implicitly related to x we have to use implicit differentiation: 3 6y = 0 y = 1 2 x ln(b) ln(b)

PROOF OF FIRST STANDARD FORM OF NONELEMENTARY FUNCTIONS

Discrete Hilbert Transform. Numeric Algorithms

First order differential equation Linear equation; Method of integrating factors

MSLC Math 151 WI09 Exam 2 Review Solutions

2008 AP Calculus BC Multiple Choice Exam

Quasi-Classical States of the Simple Harmonic Oscillator

Transcription:

Introduction Introduction to Mdical aging Lctur 4: Fourir Thory Thory dvlopd by Josph Fourir (768-83) Th Fourir transform of a signal s() yilds its frquncy spctrum S(k) Klaus Mullr s() forward transform DC (avrag) trm πik Sk ( ) Fs { ( )} s ( ) d = = Computr Scinc Dpartmnt Stony Brook Univrsity S(k) invrs transform πik s ( ) F { Sk ( )} Sk ( ) dk = = Etnsion to Highr Dimnsions Th Fourir transform gnralizs to highr dimnsions Considr th D cas: forward transform πi( k+ ly) Skl Fsy { } sy ddy invrs transform = = πi( k+ ly) sy F { S( k, l)} S( k, l) dkdl = = Calculation: ct Function + L iπk iπk S( k) = F{ AΠ ( )} = A ( ) d A d Π = L A A = = π kl πki πk = AL sinc( π kl) iπkl iπkl ( ) sin( ) Fourir pair W s that a finit signal in th -domain crats an infinit signal in th k-domain (th frquncy domain) th sam is tru vic vrsa

Proprtis Scaling: considr th rct (bo): th gratr L th highr th spctrum (factor AL) th narrowr th spctrum (factor L) th scaling rul is thrfor: k Fsa {( )} = S( ) a a Symmtry: F{ S( )} = s( k) Linarity: F{ as( ) + bs( )} = F{ as( )} + F{ bs( )} Translation: Fs {( )} = Sk ( ) πi k phas shift Convolution: Fs { ( ) s( )} = S( k) S( k) Fs { ( ) s( )} = S( k) S( k) Sk ( ) = ALsinc( π kl) a> shrinks s a< strtchs s Scaling Proprty Th rct function provids good insight into th rlationship of fin dtail and frquncy bandwidth a thin rct can rprsnt/rsolv fin dtail (think of a signal bing rprsntd as an array of thin rcts a thin rct givs ris to a wid frquncy lob this illustrats that signals with mor dtail will hav broadr frquncy spctra or, in turn, signals with thin frquncy spctra will hav low spatial rsolution Influnc of Transfr Function H W know (from th last lctur) that: ( ) ( ) πik ( ) = i s S k H k dk s ( ) = s ( ) h( ) S ( k) H( k) = S ( k) o i i o Calculation: Dirac puls For s()=δ(): iπk iπk ( ) = { ( )} = ( ) = = S k F δ δ d Lt s look at a concrt ampl: H is a lowpass (blurring) filtr: it rducs th highr frquncis of S mor than th lowr ons aftr application of H k call that th Dirac is an trmly thin rct function th frquncy spctrum is thrfor trmly broad ( vrywhr) This illustrats a ky fatur of th Fourir Transform: th narrowr th s(), th widr th S(k) sharp objcts nd highr frquncis to rprsnt that sharpnss

portant Fourir Pairs: Sinusoids Sinusoids of frquncy k giv ris to two spiks in th frquncy domain at ±k cos( πk ) ( δ( k+ k) + δ( k k)) / sin( πk) i( δ( k+ k) δ( k k)) / call th pointr analogon in th compl plan for th cos(): th ral signal is givn by th addition of th two vctors (dividd by ), projctd onto th ral ais portant Fourir Pairs: Sinusoids Sinusoids of frquncy k giv ris to two spiks in th frquncy domain at ±k cos( πk ) ( δ( k+ k) + δ( k k)) / sin( πk) i( δ( k+ k) δ( k k)) / call th pointr analogon in th compl plan for th sin(): th ral signal is givn by th addition of th two vctors (dividd by ), projctd onto th imaginary ais (not th i in th quation) -k k = -k k = Mor portant Fourir Pairs δ ( ) δ ( k) cos( πk) ( δ( k+ k) + δ( k k)) / σ sin( πk) i( δ( k+ k) δ( k k)) / Π( ) sinc( π Lk) Λ( ) Lsinc ( π Lk) k σ Som ots In th D transform, if f(,y) is sparabl, that is, f(,y)=f()f(y), on may writ: π { } ( ) πik Skl = Fsy = s y ( s( ) d) dy π ily πik sy F { S( k, l)} S() l ( s( k) dk) dl = = this coms in handy somtims th Gaussian width is invrsly rlatd

Som ots Somtims th factor πk is usd as ω: ( ) ( ) iω s ( ) = Si ω H ω dω So far, w hav only discussd th continuous spac with (potntially) infinit spctra and signals that is whr it maks sns to us ω but in rality w dal with finit, discrt signals (hr k mattrs) w shall discuss this nt Fourir Transform of Discrt Signals: DTFT Discrt-Tim Fourir Transform (DTFT) assums that th signal is discrt, but infinit S( ω) = s( n) n= + π sn ( ) = S( ω) π iωn th frquncy spctrum is continuous, but is priodic (has aliass) s(n) iωn S(ω) aliass cntrd at π Fourir Transform of Discrt Signals: DFT Discrt Fourir Transform (DFT) assums that th signal is discrt and finit Sk ( ) = sn ( ) sn ( ) = Sk ( ) iπkn iπkn n= n= now w hav only sampls, and w can calculat frquncis th frquncy spctrum is now discrt, and it is priodic in Fourir Transform in Highr Dimnsions Th D transform: Sparability: M Skl = snm m= n= m= n= i π ( kn+ lm) M M snm = Skl M i π ( kn+ lm) M s(n) S(ω) M iπlm M Skl = Pkm whr Pkm = snm M m= n= M iπlm M snm = pnl whr p( nl, ) = Snm M l= k= if M=, complity is O( 3 ) iπ kn iπ kn

Fast Fourir Transform () cursivly braks up th FT sum into odd and vn trms: Fast Fourir Transform () Givs ris to th wll-known buttrfly architctur: iπkn / iπkn / i πk(n+ ) Sk ( ) = sn ( ) = s( n ) + s(n+ ) n= n= n= / iπkn iπk / iπkn / / svn() n sodd () n n= n= = + sults in an O(n log(n)) algorithm (in D) O(n log(n)) for D (and so on)