DREAM PLAN IDEA IMPLEMENTATION 1. 2 3 Introduction to Image Processing Dr. Kourosh Kiani

Slides:



Advertisements
Similar presentations
DCSP-5: Noise Jianfeng Feng Department of Computer Science Warwick Univ., UK
Advertisements

DCSP-22 Jianfeng Feng Department of Computer Science Warwick Univ., UK
1 DREAM PLAN IDEA IMPLEMENTATION. 2 3 Introduction to Image Processing Dr. Kourosh Kiani
DREAM PLAN IDEA IMPLEMENTATION Introduction to Image Processing Dr. Kourosh Kiani
DREAM PLAN IDEA IMPLEMENTATION Introduction to Image Processing Dr. Kourosh Kiani
Matlab Tutorial. Session 1 Basics, Filters, Color Space, Derivatives, Pyramids, Optical Flow Gonzalo Vaca-Castano.
1 A L L A H. Command-Window Workspace & Directory Command- History The Matlab Command window - Finding your way around.
Automation and Drives SIMATIC HMI The Human Machine Interface for internal use only Scope of Presentation Dept. of Industrial Electronics and Control Eng.
Neighborhood Processing
Image Processing. Image processing Once we have an image in a digital form we can process it in the computer. We apply a “filter” and recalculate the.
Image Display MATLAB functions for displaying image Bit Planes
7.1Variable Notation.
MATLAB Image Processing Toolbox. Introduction  Collection of functions (MATLAB files) that supports a wide range of image processing operations  Documentation.
DREAM PLAN IDEA IMPLEMENTATION Introduction to Image Processing Dr. Kourosh Kiani
DREAM PLAN IDEA IMPLEMENTATION Introduction to Image Processing Dr. Kourosh Kiani
DREAM PLAN IDEA IMPLEMENTATION Introduction to Image Processing Dr. Kourosh Kiani
Physics Rules for using Significant Figures. Rules for Averaging Trials Determine the average of the trials using a calculator Determine the uncertainty.
Image Analysis Preprocessing Arithmetic and Logic Operations Spatial Filters Image Quantization.
DREAM PLAN IDEA IMPLEMENTATION Introduction to Image Processing Dr. Kourosh Kiani
3.2 Solving Systems of Equations Algebraically Substitution Method Elimination Method.
Taks Objective 2 Properties and attributes of function.
Solve the equation -3v = -21 Multiply or Divide? 1.
DREAM PLAN IDEA IMPLEMENTATION Introduction to Computer Graphics Dr. Kourosh Kiani
Image Arithmetic Image arithmetic is the implementation of standard arithmetic operations, such as addition, subtraction, multiplication, and division,
CS 450: Introduction to Digital Signal and Image Processing Image Arithmetic.
Algebra 11.7 Dividing Polynomials. 9x² 3x 18 3x 12x 3x Dividing a Polynomial by a Monomial Divide 9x² + 12x – 18 by 3x 9x² + 12x – 18 3x =
Chapter 5.1 Exponent Properties #34 Mathematics is like love; a simple idea, but it can get complicated.” unknown.
Integer Exponents Rules for Exponents Unit 1, Lesson 5.
Translating Algebraic and Verbal Expressions. Warm Up Answer the following problems 1.(5+2-6) - (1-5+12) + (6-3+11)= 2.2(5-3) 2 + (15÷3x2) - (5+2 x 1-4)=
CMPS1371 Introduction to Computing for Engineers IMAGES.
TRANSLATING Word phrases to algebraic expressions.
Algebra Review Positive and Negative Numbers Great Marlow School Mathematics Department.
CHAPTER 4 Negative Numbers. ADDITION AND SUBTRACTION USING NEGATIVE NUMBERS A number line is very useful when you have to do additions or subtractions.
Precision in measurement. Significant Figures The number of digits that have meaning to precision of data Rules 1. All non-zero numbers ARE significant.
What are Indices? Indices provide a way of writing numbers in a more convenient form Indices is the plural of Index An Index is often referred to as a.
$100 $200 $300 $400 $100 $200 $300 $400 $300 $200 $100 Writing variable equations Find variables in addition equations Find variables in subtraction.
Multiplication and Division Properties. Multiplication Properties Commutative Property Associative Property Identity Property Zero Property Distributive.
Algebraic Properties Terra Alta/East Preston School Terra Alta, West Virginia.
 Commutative Property of Addition  When adding two or more numbers or terms together, order is NOT important.  a + b = b + a  =
Exponent Properties Product of Powers: 23 ● 22 = 23+2 = 25
Computer Application in Engineering Design
Multiplying 2 Digit Factors
Variables and Expressions
Multiplying and Dividing Integers
Introduction to Algebra
The Chinese University of Hong Kong
Algebraic Properties.
College Algebra 1.5 Complex Numbers
Variables and Expressions
Solving Systems Using Elimination
Algebraic Properties in solving equations
Solving Algebraic Equations
SIGNIFICANT DIGIT RULES
Unit 3 Lecture 24 Algebraic Fractions
Introduction to Variables, Algebraic Expressions, and Equations
Rules for Determining Significant Figures
Two Step Equation.
Equation with variables on both sides
Two step equation Operations
Hundred Dollar Questions
Two step equation Brackets
Algebraic expression to verbal statement two terms
Fundamentals of Image Processing Digital Image Representation
Introduction to Mathematical tools in used in DIP
Multiply and divide Expressions
Math-7 NOTES What are Two-Step Equations??
DIRECTED NUMBERS.
Algebra with Whole Numbers
Lecture 7 Spatial filtering.
Image Enhancement in Spatial Domain: Point Processing
Presentation transcript:

DREAM PLAN IDEA IMPLEMENTATION 1

2

3 Introduction to Image Processing Dr. Kourosh Kiani Web: Present to: Amirkabir University of Technology (Tehran Polytechnic) & Semnan University

Lecture 04 4

Algebraic operations used for images are commonly viewed in two groups; mathematical and logical operations. Image adding, subtracting, dividing and multiplying operations constitute mathematical processing and “AND, OR, NOT” etc. operations forms logical operations. SIMPLE ALGEBRAIC OPERATIONS in IMAGES

……… …a4a3 …a2a1 ……… …b4b3 …b2b1 a4 +b4 a3 +b3 a2 +b2 a1 +b1 + = ……… …a4a3 …a2a1 a4 +10 a3 +10 a2 +10 a = 10

Reduce noise (increase SNR) averaging, smoothing =

I = imread(‘rice.tif’); J = imread(‘cameraman.tif’); K = imadd(I, J); imshow(K) Or i=imread('rice.png'); j=imread('cameraman.tif'); k=i+j; imshow(k);

I = imread('kourosh.jpg'); figure(1); imshow(I); I2 = imadd(I, 70); figure(2); imshow(I2); + 70 =

Image Averaging  Consider a noisy image g(x,y) formed by the addition of noise  (x,y) to an original image f(x,y) g(x,y) = f(x,y) +  (x,y)

Image Averaging  If noise has zero mean and is uncorrelated then it can be shown that = image formed by averaging K different noisy images

Image Averaging  Then = variances of g and   Then if K increase, it indicates that the variability (noise) of the pixel at each location (x,y) decreases.

 Average multiple images (frames) of the same scene together  Useful for removing noise =

X = Y = Z = X = uint8([ ; ]); Y = uint8([ ; ]); Z = imsubtract(X,Y) Image Subtracting

rice = imread('rice.png'); figure (1) imshow(rice); background = imopen(rice, strel('disk', 15)); figure (2) imshow(background); rice2 = imsubtract(rice, background); figure (3) imshow(rice2); - =

- 70 = I = imread('kourosh.jpg'); J = imsubtract(I,70); Figure(1), imshow(I), Figure(2), imshow(J) Image Subtracting

_ = Digital subtraction angiography (DSA) Image Subtracting

Digital subtraction angiography (DSA) Image Subtracting

X = Y = Z = X = uint8([ ; ]); Y = uint8([ 5 5 5; ]); Z = immultiply(X,Y) Image Multiplying

I = imread('moon.tif'); figure(1) imshow(I) J = immultiply(I,0.5); figure(2) imshow(J) * 0.5 =

X = Y = Z = X = uint8([ ; ]) Y = uint8([ 5 5 5; ]) Z = imdivide(X,Y) Image Dividing

I = imread('rice.png'); figure(1), imshow(I); background = imopen(I,strel('disk',15)); figure(2), imshow(background); Ip = imdivide(I,background); figure(3), imshow(Ip, []); ÷ =

Image Dividing ÷ 2 = I = imread('rice.png'); J = imdivide(I,2); figure(1), imshow(I) figure(2), imshow(J)

Questions? Discussion? Suggestions ?

26