Digital Image Processing

Similar documents
DIGITAL IMAGE PROCESSING LECTURE # 4 DIGITAL IMAGE FUNDAMENTALS-I

Chapter 2: Digital Image Fundamentals. Digital image processing is based on. Mathematical and probabilistic models Human intuition and analysis

Introduction to Visual Perception & the EM Spectrum

Review. Introduction to Visual Perception & the EM Spectrum. Overview (1):

Lecture 2 Digital Image Fundamentals. Lin ZHANG, PhD School of Software Engineering Tongji University Fall 2016

Human Visual System. Prof. George Wolberg Dept. of Computer Science City College of New York

STUDY NOTES UNIT I IMAGE PERCEPTION AND SAMPLING. Elements of Digital Image Processing Systems. Elements of Visual Perception structure of human eye

Unit 1 DIGITAL IMAGE FUNDAMENTALS

EC-433 Digital Image Processing

III: Vision. Objectives:

Visual Perception of Images

The Special Senses: Vision

The human visual system

Vision Science I Exam 1 23 September ) The plot to the right shows the spectrum of a light source. Which of the following sources is this

10/8/ dpt. n 21 = n n' r D = The electromagnetic spectrum. A few words about light. BÓDIS Emőke 02 October Optical Imaging in the Eye

LIGHT AND LIGHTING FUNDAMENTALS. Prepared by Engr. John Paul Timola

Work environment. Retina anatomy. A human eyeball is like a simple camera! The way of vision signal. Directional sensitivity. Lighting.

EYE ANATOMY. Multimedia Health Education. Disclaimer

Further reading. 1. Visual perception. Restricting the light. Forming an image. Angel, section 1.4

Image Processing - Intro. Tamás Szirányi

The Human Eye and a Camera 12.1

11/23/11. A few words about light nm The electromagnetic spectrum. BÓDIS Emőke 22 November Schematic structure of the eye

Digital Image Processing

Vision. The eye. Image formation. Eye defects & corrective lenses. Visual acuity. Colour vision. Lecture 3.5

Vision. Biological vision and image processing

AP PSYCH Unit 4.2 Vision 1. How does the eye transform light energy into neural messages? 2. How does the brain process visual information? 3.

Radiometric and Photometric Measurements with TAOS PhotoSensors

Visual Optics. Visual Optics - Introduction

SCIENCE 8 WORKBOOK Chapter 6 Human Vision Ms. Jamieson 2018 This workbook belongs to:

Work environment. Vision. Human Millieu system. Retina anatomy. A human eyeball is like a simple camera! Lighting. Eye anatomy. Cones colours

Reading. 1. Visual perception. Outline. Forming an image. Optional: Glassner, Principles of Digital Image Synthesis, sections

Fundamentals. Preview 2.1. Elements of Visual Perception. Those who wish to succeed must ask the right preliminary questions.

Seeing and Perception. External features of the Eye

Science 8 Unit 2 Pack:

Digital Image Processing COSC 6380/4393. Lecture 20 Oct 25 th, 2018 Pranav Mantini

Physical Science Physics

Vision and Color. Reading. Optics, cont d. Lenses. d d f. Brian Curless CSE 557 Autumn Good resources:

Vision and Color. Brian Curless CSE 557 Autumn 2015

Digital Image Processing COSC 6380/4393

Visual System I Eye and Retina

Visual Effects of Light. Prof. Grega Bizjak, PhD Laboratory of Lighting and Photometry Faculty of Electrical Engineering University of Ljubljana

Vision and Color. Reading. Optics, cont d. Lenses. d d f. Brian Curless CSEP 557 Fall Good resources:

Vision and Color. Brian Curless CSEP 557 Fall 2016

Vision and Color. Reading. The lensmaker s formula. Lenses. Brian Curless CSEP 557 Autumn Good resources:

SCIENCE 8 WORKBOOK Chapter 6 Human Vision Ms. Jamieson 2018 This workbook belongs to:

Vision. PSYCHOLOGY (8th Edition, in Modules) David Myers. Module 13. Vision. Vision

CS 548: Computer Vision REVIEW: Digital Image Basics. Spring 2016 Dr. Michael J. Reale

Capturing Light in man and machine. Some figures from Steve Seitz, Steve Palmer, Paul Debevec, and Gonzalez et al.

Visual Effects of. Light. Warmth. Light is life. Sun as a deity (god) If sun would turn off the life on earth would extinct

Digital Image Processing

We have already discussed retinal structure and organization, as well as the photochemical and electrophysiological basis for vision.

Sensory receptors External internal stimulus change detectable energy transduce action potential different strengths different frequencies

Color Image Processing. Gonzales & Woods: Chapter 6

Early Visual Processing: Receptive Fields & Retinal Processing (Chapter 2, part 2)

Reading. Lenses, cont d. Lenses. Vision and color. d d f. Good resources: Glassner, Principles of Digital Image Synthesis, pp

Eye. Eye Major structural layer of the wall of the eye is a thick layer of dense C.T.; that layer has two parts:

Chapter Human Vision

The Human Visual System. Lecture 1. The Human Visual System. The Human Eye. The Human Retina. cones. rods. horizontal. bipolar. amacrine.

Human Visual System. Digital Image Processing. Digital Image Fundamentals. Structure Of The Human Eye. Blind-Spot Experiment.

The Science Seeing of process Digital Media. The Science of Digital Media Introduction

The eye* The eye is a slightly asymmetrical globe, about an inch in diameter. The front part of the eye (the part you see in the mirror) includes:

HW- Finish your vision book!

For a long time I limited myself to one color as a form of discipline. Pablo Picasso. Color Image Processing

Digital Image Processing

Digital Image Processing

Fig Color spectrum seen by passing white light through a prism.

Sensation. What is Sensation, Perception, and Cognition. All sensory systems operate the same, they only use different mechanisms

Sensation. Sensation. Perception. What is Sensation, Perception, and Cognition

Digital Image Fundamentals. Digital Image Processing. Human Visual System. Contents. Structure Of The Human Eye (cont.) Structure Of The Human Eye

Digital Image Fundamentals. Digital Image Processing. Human Visual System. Contents. Structure Of The Human Eye (cont.) Structure Of The Human Eye

Physics 1230: Light and Color. Guest Lecture, Jack again. Lecture 23: More about cameras

Why is blue tinted backlight better?

Photography (cont d)

Digital Image Processing

CPSC 4040/6040 Computer Graphics Images. Joshua Levine

Vision. By: Karen, Jaqui, and Jen

Chapter Six Chapter Six

General Imaging System

Visual Perception. human perception display devices. CS Visual Perception

Digital Image Processing COSC 6380/4393

COLOR and the human response to light

Capturing Light in man and machine

Vision Basics Measured in:

Lecture 8. Human Information Processing (1) CENG 412-Human Factors in Engineering May

EYE STRUCTURE AND FUNCTION

Chapter 6 Human Vision

Acquisition and representation of images

Light and sight. Sight is the ability for a token to "see" its surroundings

Visibility, Performance and Perception. Cooper Lighting

Color & Graphics. Color & Vision. The complete display system is: We'll talk about: Model Frame Buffer Screen Eye Brain

Image Processing for Mechatronics Engineering For senior undergraduate students Academic Year 2017/2018, Winter Semester

Image Processing. Michael Kazhdan ( /657) HB Ch FvDFH Ch. 13.1

DIGITAL IMAGE PROCESSING (COM-3371) Week 2 - January 14, 2002

Image and Multidimensional Signal Processing

PHGY Physiology. The Process of Vision. SENSORY PHYSIOLOGY Vision. Martin Paré. Visible Light. Ocular Anatomy. Ocular Anatomy.

Introduction. Chapter Aim of the Thesis

Capturing Light in man and machine

PHGY Physiology. SENSORY PHYSIOLOGY Vision. Martin Paré

Yokohama City University lecture INTRODUCTION TO HUMAN VISION Presentation notes 7/10/14

Graphics and Image Processing Basics

Transcription:

Digital Image Processing Lecture # 3 Digital Image Fundamentals

ALI JAVED Lecturer SOFTWARE ENGINEERING DEPARTMENT U.E.T TAXILA Email:: ali.javed@uettaxila.edu.pk Office Room #:: 7

Presentation Outline Visual Perception Structure Of Human Eyes Image Formation on the Eye Brightness Adaptation and Discrimination Light and EM Spectrum Image Acquisition Image Acquisition using Point Sensor Image Acquisition using Line Sensor Image Acquisition using Array Sensor

Visual Perception How images are formed in the eye? Eye s physical limitation? Human visual interpretation of images?

Structure of Human Eyes

Structure of Human Eyes Three membranes enclose the eye: Cornea and sclera Cornea is a tough, transparent tissue cover the anterior surface of the eye. Sclera is a opaque membrane enclose the remainder of the optic globe. Choroid A network of blood vessels for eye nutrition At its anterior extreme, it is divided into the ciliary body and iris diaphragm. The central opening (the pupil) varies in diameter from 2 to 8 mm. Retina Retina lines the insides of the wall s interior portion with two classes of receptors:

Structure of Human Eyes Eye Sensors We see the scene with the sensors in the retina of the eye called rods and cones Color Sensor Cones: (Red 65%, Green 33%,Blue 2%) 6 7 millions located primarily in the central portion of the retina Highly sensitive to color Photopic or bright-light vision Rods Brightness Sensor 75-150 millions distributed over the retinal surface. Not involved in color vision and sensitive to low illumination Scotopic or dim vision

Structure of Human Eyes Eye Sensors [Rods] Rods are more sensitive than the cones but they are not sensitive to color, they perceive images as black, white and different shades of grey. They work well in dim light as they contain a pigment, rhodopsin, which is sensitive at low light intensity, but saturates at higher (Photopic) intensities. More than one thousand times as sensitive, the rods respond better to blue but very little to red light Rods are distributed throughout the retina but there are none at the fovea and none at the blind spot. Rod density is greater in the peripheral retina than in the central retina.

Structure of Human Eyes Eye Sensors [Cones] Each cone contains one of three pigments sensitive to either RED GREEN or BLUE Each pigment absorbs a particular wavelength of color. There are short wavelength cones that absorb blue light, middle wavelength cones that absorb green light, and long wavelength cones that absorb red light When we observe a color that has a wavelength between that of the primary colors red, green and blue, combinations of the cones are stimulated. An example could be that yellow light stimulates cones that are sensitive to red and to green light. The result is that we can detect light of all colors in the visible spectrum People who suffer color blindness have less numbers of particular cones than normal, so they get colors confused.

Structure of Human Eyes The cones are most dense in the center of retina. Density of cones in the area of fovea is 150,000 element/mm2 The number of cones in fovea is 337,000 elements.

Image Formation in the Eyes The distance between the center of the lens and the retina (focal length) varies from 17mm to 14mm. The shape of lens is controlled by the tension of fibers of the ciliary body. The retinal image is reflected primarily in the area of fovea. Perception = excitation of light receptors, which transform radiant energy into electrical impulses that are ultimately decoded by the brain.

Image Formation in the Eyes

Brightness Adaptation & Discrimination The range of light intensity levels to which the human visual system can adapt is enormous on the order of 10^10. The subjective brightness is a logarithmic function of light intensity incident on the eye. In photopic vision, the range is about 10^6. The current sensitivity level it can discriminate simultaneously is rather small compared with the total adaptation range Brightness adaptation level: the current sensitive level of the visual system.

Brightness Adaptation & Discrimination

Brightness Adaptation & Discrimination

Brightness Adaptation & Discrimination The dic is the increment of illumination discriminable 50% of the time with the background illumination I. The quantity dic/i is called the Weber ratio. The smaller dic/i means that a small percentage change in intensity is discriminable good brightness discrimination If the background illumination is constant, the intensity of object is allowed to vary incrementally from never perceived to always being perceived. Typically the observer can discern a totally from one to two dozens different intensity changes. The number of gray level for digital image Contouring Effect: Not sufficient no. of gray levels

Brightness Adaptation & Discrimination Perceived brightness is not a simple function of intensity, rather it is log of intensity

Brightness Adaptation & Discrimination A region s perceived brightness does not simply depend on its intensity but also on the background Simultaneous contrast.

Light & EM Spectrum

Light & EM Spectrum Light is a particular type of EM radiation that can be seen by human eye. EM waves are massless particles each traveling in a wavelike pattern and moving at a speed of light. We can specify waves through frequency and wavelength. The colors that human perceive in an object are determined by the nature of the light reflected from the object. For example green objects reflect light with wavelengths primarily in the 500 to 570nm range while absorbing most of the energy at other wavelengths.

Achromatic Light Light & EM Spectrum Light that is void of color is called achromatic or monochromatic light The only attribute of such light is its intensity. The term gray level generally is used to describe monochromatic intensity because it ranges from black to grays and finally to white Chromatic light spans EM spectrum from 0.43 um (violet) to 0.79 um ( red). Three basic quantities are used to describe the quality of a chromatic light source 1. Radiance 2. Luminance 3. Brightness

Light & EM Spectrum Radiance The total amount of energy that flows from the light source Measured in Watts(W) Luminance Gives a measure of the amount of energy an observer perceives from the a light source. Measured in Lumens (lm) or Candela per square meter (cd/m2) For example light emitted from a source operating in a far infrared region of the spectrum could have significant energy (radiance) but an observer would hardly perceive it; its luminance would be hardly zero Brightness Subjective descriptor of light perception that is practically impossible to measure

Image Acquisition

Image Acquisition using Point Sensor Specify the location of vertical and horizontal motors Sense the light reflection Voltage waveform will be received (Analog signal) Convert this analog signal into digital signal through sampling and quantization Apply Sampling to digitize coordinate values Apply Quantization to digitize amplitude values Store the digitized value in memory

Image Acquisition using Point Sensor

Image Acquisition using Line Sensor Specify the location of vertical motor Sense the light reflection Voltage waveform will be received (Analog signal) Convert this analog signal into digital signal through sampling and quantization Apply Sampling to digitize coordinate values Apply Quantization to digitize amplitude values Store the digitized value in memory

Image Acquisition using Line Sensor

Image Acquisition using Array Sensor Figure shows individual sensors arranged in a form of 2-D array This arrangement exists in modern day digital cameras A typical sensors for these cameras is a CCD array, which can be manufactured with a broad range of sensing properties and can be packaged in arrays of 4000 x 4000 elements or more CCD sensors are used widely in digital cameras and other light sensing instruments The response of each sensor is proportional to the integral of the light energy projected on to the surface of the sensor

Image Acquisition using Array Sensor Sense the light reflection on the sensor (arranged in 2D form) Voltage waveform will be received (Analog signal) Convert this analog signal into digital signal through sampling and quantization Apply Sampling to digitize coordinate values Apply Quantization to digitize amplitude values Store the digitized value in memory

Any question