SPIE Programmes
ELECTRONIC IMAGING
- Use of CCDs in Visible Imaging
Applications
- Introduction to Electronic Imaging
- Applications of Modern Image
Processing
- Image Processing and Analysis
Use of CCDs in Visible Imaging Applications
Instructor: Dr. Terrence S. Lomheim
is a Senior Engineering Specialist at The Aerospace Corporation.
Dr. Lomheim has 18 years of hardware and analysis experience in
visible and infrared electro-optical systems, focal plane
technology, and applied optics. He has held both technical staff
and management positions during his career, and was the recipient
of the Aerospace Corporation President's Award for engineering in
1985.
This course will describe the capabilities of
visible charge-coupled device (CCDs) and other similar solid
state imagers (CIDs, active pixel sensors) and illustrate their
use with examples spanning a diverse range from commercial
scanning to satellite imaging. Several important topics covering
key solid state sensor concepts are first introduced and
developed. This foundation is then used to discuss and illustrate
the use of CCDs and solid state sensors for specific
applications.
This course will enable you to:
- Understand the fundamentals of CCD imaging
operation, charge packet formation, charge multiplexing
and transport, and charge-to-voltage conversion
- Describe image formation, signal
manipulation and processing, and noise effects for
conventional and intensified (low-light level) imaging
systems
- Understand and compare CCDs and other
competing visible imaging device architectures [e.g. the
Active Pixel Sensor (APS) and the Charge Injection Device
(CID)]
- Describe the CCD signal chain through
analog-to-digital conversion
- Define complete signal and noise models
for CCD and other visible imaging systems
- Analyze system imaging capability by using
the system modulation transfer function (MTF) and
signal-to-noise ratio
- Describe detailed example of tailoring a
CCD sensor system to the specific applications of
commercial film scanning and satellite imaging
- List important technical criteria for
specifying the design/fabrication of a state-of-the-art
CCD or visible imaging device
- Understand how to experimentally
characterize a CCD in order to verify its key performance
measures
- Have access to a fairly complete
bibliography on CCDs and visible imaging devices
Part I: Introduction and CCD Basics
- Survey major CCD and solid state sensor
applications
- Describe the CCD concept-of-operation and
charge transport basics
- Explain fundamental CCD signal and noise
properties
- Describe principal CCD architectures
- Discuss strengths and weaknesses of CIDs
and active pixel sensors
Part II: CCD Signal Processing and
Modulation Transfer Function Basics
- Define array timing relationships
- Explain the CCD signal processing chain
- Describe signal chain optimization,
correlated-double-sampling (CDS), and
time-delay-integration (TDI)
- Define basic MTF concepts
- Distinguish optical system, CCD detector
aperture, CCD carrier diffusion, and image motion smear
components of the "system MTF"
- Describe spatial sampling and aliasing
effects
Part III: Image Sensor Design ad
Optimization Using Signal/Noise and MTF Models
- Explain flow-down of system requirements
to sensor/CCD parameters
- Develop and describe CCD sensor signal and
noise models
- Discuss and illustrate the impact of
signal/noise and MTF on imaging capability
Part IV: Example Applications of CCD
Technology
- Describe in detail the design of a
multi-spectral CCD-based satellite imaging system
- Describe in detail a commercial film
scanning system: HDTV to Telecine converter
Part V: Specification and Measurement of
CCDs/Image Intensified CCD Camera
- Discuss important technical issues in
contracting for CCD development and fabrication
- Overview key electro-optical specification
for CCDs
- Describe CCD experimental characterization
techniques
- Describe image intensified CCD technology
and performance
Intended Audience: Engineers,
scientists, students, and managers who are interested in
utilizing CCD and solid state sensor technology in advanced
imaging applications. An undergraduate degree in engineering,
physics, math, computer science or equivalent work experience
and/or training is recommended. Familiarity with basic topics in
semiconductor physics/engineering, image formation, and
radiometry will enhance student understanding of the course
concepts.
Order Number: VT120496
Length: 5 hours
Individual Price: Lisst US$395
Site License: Lisst US$1,000
Introduction to Electronic Imaging
Instructor: Majid Rabbani is a part of
the Eastman Kodak Research Labs. in Rochester, NY, where he is
currently a Research Associate and the head of the Image
Compression Technology Area.
This course is an introduction to the basic
concepts as well as applications of the rapidly emerging field of
electronic imaging and digital image processing. It familiarizes
the audience with the various components of the electronic
imaging chain, namely, capture, processing, storage,
transmission, and output, and explains the various technologies
that serve these components with particular focus on the capture
and processing techniques. Numerous image examples complement the
description.
This course will enable you to:
- List the various components of the
electronic imaging chain and compare the various
technologies that serve them
- Define the fundamental concepts employed
in digital imaging such as sampling, perceptual
quantization, aliasing, FIR filtering, interpolation,
subsampling, histogram, etc.
- Describe the various digital image capture
technologies and their applications
- Describe the techniques used for the
manipulation and enhancement of images such as contrast
manipulation, sharpening, and noise and blur removal
- Describe the basic building blocks of
image compression techniques used for the efficient
storage and transmission of images and video, such as
JPEG, MPEG, photo CD compression
- Describe the various image storage
technologies and their applications.
Part I: Introduction and Image Capture
- Define the electronic imaging chain and
its components
- Explain and demonstrate the processes of
sampling and quantization for image digitization
- Present examples of various digital images
and define the various terminologies used in digital
imaging
- Describe the CCD-based image capture
technologies used in digital cameras and electronic
camcorders
- Explain the use of color filter arrays
(CFA) in digital cameras
Part II: Image Capture/Processing
- Describe the various scanning methods used
for image digitization
- Explain and demonstrate the aliasing
phenomenon resulting from inadequate image sampling
- Describe and demonstrate perceptually
uniform quantization of image pixel values
- Explain how color images are represented
and show examples of RGB and luminance-chrominance
representations
- Define look-up-table, local, and global
image transformations
- Define FIR image filtering and illustrate
the effect of low-pass and high-pass image filters via
image examples
Part III: Digital Image Processing
- List the various subareas of digital image
processing
- Briefly explain digital image editing and
manipulation
- Define the goal of image understanding and
demonstrate representative algorithms with image examples
- Define the goal of image enhancement
- Describe and illustrate contrast
enhancement algorithms such as adaptive and nonadaptive
histogram equalization
- Describe and illustrate sharpening
algorithms such as high-pass filtering and adaptive and
nonadaptive unsharp masking
- Describe and illustrate noise reduction
algorithms such as K-NN and median filtering
Part IV: Digital Image Compression
- Define the goal of image compression
- Establish the need for digital image and
video compression through product examples
- Explain the main building blocks of a
generic compression algorithm, namely, transformation,
quantization, and coding
- Explain the image compression scheme
employed in the Photo CD system
- Briefly review the scope and the current
status of emerging international standards for image and
video compression
- Briefly explain the JPEG and MPEG image
compression standards and demonstrate their performance
via image examples
Part V: Digital Image Storage and Transmission
- List the various digital image storage
technologies and provide representative examples
- Define the performance criteria for
digital storage media and use that to compare the
existing technologies
- Define the various digital image
transmission technologies such as local and wide area
networks
- Summarize image transmission performance
by tabulating the amount of time required to transmit
various images using the existing technologies
- List the various image hardcopy
technologies and compare them based on relevant
performance criteria
Intended Audience: Scientists, engineers and
technicians with little or no background knowledge in electronic
imaging or digital image processing. Managers, product planners,
and marketing people charged with the development or marketing of
electronic imaging systems or charged with the assessment of the
impact of this technology on current and future products.
Order Number: VT051895
Length: 5 hours
Individual Price: Lisst US$395
Site License: Lisst US$1,000
Applications of Modern Image Processing
Harley R. Myler is currently an
Associate Professor in the department of Electrical and Computer
Engineering at the University of Central Florida in Orlando.
Arthur R. Weeks is an assistant professor of Electrical and
Computer Engineering at the University of Central Florida,
Orlando, FL.
This program will cover the entire range of
fundamental image processing algorithms as required by the
imaging scientist and engineer. Specifically, spatial and
frequency filtering methods used to remove unwanted noise from
images, graylevel enhancement methods (histogram equalization and
specification and contrast stretching) used to improve the
overall appearance of an image, image degradation models and
Wiener filtering used in image restoration, and a survey of image
understanding algorithms covering segmentation, thresholding,
morphological processing and edge techniques. The focus of this
course will be on the understanding of applied image processing
as it relates to research and development in the commercial,
military and academic sectors.
Completion of this program will allow you to:
- Understand the fundamentals of image
processing such as image characterization, spatial
sampling, and graylevel quantization
- Analyze and solve image restoration and
enhancement problems
- Understand basic image processing
algorithms and their capabilities, limitations and
application
- Evaluate and use PC and workstation-based
image analysis packages.
Part I: Introduction to Digital Image
Processing
- Understand human visual perception
mechanisms and their relationship to imaging.
- Define image characterization and image
data formats.
- Differentiate between image sampling and
quantization and identify needs related to image
acquisition and display.
Part II: Image Transforms
- Define and compute Discrete Fourier and
Cosine Transforms
- Explain and summarize basic Fourier
Transform properties
- Define and compute Walsh and Hadamard
Transforms
- Define and compute the Hough Transform
- Identify uses and applications of the
transforms discussed
Part III: Image Enhancement
- Apply spatial and frequency domain
techniques to image problems
- Understand and compute histogram methods
of image processing
- Distinguish and explain nonlinear and
adaptive filtering approaches
Part IV: Image Restoration
- Classify and define image degradation
models
- Apply and use inverse filtering techniques
for restoration
- Understand and apply Wiener filtering
Part V: Image Understanding
- Explain segmentation and thresholding
approaches to image object extraction
- Understand and apply morphological filters
to extracted objects
- Evaluate and compute edge detection and
enhancement approaches
- Summarize representation and
classification methods
Intended Audience: Engineers and
scientists requiring image processing in their activities for the
acquisition, evaluation and enhancement of digital images. No
previous training or experience in image processing is necessary.
The program will be of particular interest to managers of
facilities or programs currently using imaging, or considering
adding image or media processing to their activities.
Order Number: VT041593
Length: 5 hours
Individual Price: Lisst US$395
Site License: Lisst US$1,000
Image Processing and Analysis
Mohan M. Trivedi is professor of
Electrical and Computer Engineering at the University of
Tennessee, Knoxville, where he established the Computer Vision
and Robotics Research (CVRR) Laboratory.
Applications for image processing can be found
in a wide range of fields such as medical diagnosis, remote
sensing, robot vision, and industrial inspection and automation
systems. This course will provide an overview of basic concepts
and techniques of digital image processing. The primary focus of
the presentation will be on low level, general purpose image
processing techniques and their applications in the development
of machine vision systems.
This course will allow you to:
- Understand the utility of various image
processing functions
- Understand the difference between spatial
domain and frequency (domain) approaches to image
processing
- Appreciate the role of mathematical
transforms in image processing
- Become familiar with and evaluate various
image enhancement, image restoration, and image
segmentation approaches
- Become familiar with applications of a
selected range of image processing and analysis
applications, mainly from the remote sensing and robot
vision domains.
Part I: Introduction to Digital Image
Processing
- Discuss utility and give examples of image
processing
- Define image processing, pattern
recognition, and machine vision
- Discuss image acquisition, sensors,
representation, and image processing workstations
- Compare spatial domain to transform
(frequency) domain
- Show mathematical transforms
Part II: Image Enhancement
- Examine spatial domain approaches:
histogram modification (including equalization and
specification),
- Neighborhood operations
- Examine transform domain approaches:
lowpass filtering, highpass filtering, homomorphic
filtering
Part III: Image Enhancement (continued) and
Image Restoration
- Illustrate image enhancement by pseudo
coloring
- Describe what image restoration is
- Describe restoration based on inverse
filtering
- Explain interactive restoration
Part IV: Image Segmentation
- Define image segmentation and describe how
it is done
- Describe region based image segmentation:
thresholding and cluster analysis
- Explain edge detection
- Describe boundary formation and Hough
transforms
Part V: Case studies in Image Analysis
- Present multiresolution (pyramid) approach
for image segmentation
- Describe quantitative texture analysis
- Summarize digital image processing
concepts and techniques
- Present various digital image processing
applications
Intended Audience: Practicing engineers
and scientists who need basic familiarity with the digital image
processing field. Persons interested in evaluating the potential
for developing machine vision system may also benefit from this
course.
Order Number: VT040893
Length: 5 hours
Individual Price: Lisst US$395
Site License: List US$1,000
