Syllabus for

CS311– Image Processing in Java

Course Description:

A first course in Image Processing; Image algebra,arithmetic operations,boolean operations, matrix operations

Achromatic and Colored Light

Selecting Intensities, Gamma Correction

Chromatic Color, psychophysics, Color models

Color Space Conversion, low-level pattern recognition.

Students will learn the theory of 2-D Fast Fourier Transform Class, 2D convolution and frequency space processing, compression and 2D streaming.

Students will apply the theory by creating programs that read processing and write image streams. They are exposed to the elements of multi-resolution multi-media network streaming. They learn about a wide class of transforms, including Wavelets, DCT, the PFA FFT and others.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Students will learn enough signal processing to write their image processing applications.

Prerequisite: ..................................... CR310, Voice and Signal Processing

Textbook:................................. Image Processing, in Java by Douglas Lyon

Reference Material:............. Java Digital Signal Processing, By Lyon and Rao

E-mail...................................................... access is required.

Computer Usage: ........ Students MUST have access to a computer with Java .

Course Notes: .......................... Handouts/diskettes/e-mail, web page

Contact Information

Phone ........................................................................ (203)641-6293

Fax ........................................................................... (203)877-4187

E-mail:................................................................ lyon@DocJava.com

Web: ............................................................. http://www.DocJava.com

Office Hours

Monday, Tuesday....................................................... 1:00 pm - 2:00 pm

Wednesday............................................................... 5:00 pm - 6:30 pm

Course Offerings

CR311, Image Processing, ....................................... Mc 203 Mon 2:00-4:00

CR 325, Computer Graphics, ................................... Mc 203 Tues 2:00-4:00

SW 409, Java Programming II................................... Mc 203 Wed 6:30-9:20

Course Objectives:

This course is designed to support the signal processing and computer systems domain in the Computer Engineering program. When the course is done, Students will have written their own Java applications for doing image processing.

1. The students will learn the principles of Image Processing.

Expected learning outcomes:

a. Applies transform concepts in programming situations

b. Recognizes interrelationships among signals and spectra

2. The student will become proficient with the usage of the Java language.

Expected learning outcomes:

a. Demonstrates the ability to utilize Java in practical image processing problems.

b. Uses appropriate object-oriented design patters to solve problems.

After the student take this course, they will know how to write programs that display and manipulate 2D images. They will also have a basic understanding of image filtering. Finally, the students will make use of data structures, linear algebra, design patterns, voice and 1D signal processing.

This course requires substantial programming effort and emphasis is place on good software engineering practices.

Outcomes:

When the course is done, Students will have deployed Java applications of their own design, on the web.

Performance Indicators:

Aside from the basics assessment procedures based on homeworks and tests, Students must obtain 75% or better on all tests. Additionally, students must perform at least 75% on the homeworks.

Student Activities: Learning a new computer language is very much a hands-on activity, which cannot be learned from lectures or textbook reading alone. It does require those lectures and textbooks, but the real learning results from the laboratory trials and the homework assignments. To achieve the course objectives, the student must have good class attendance and participation, conduct the computer programming tasks during the laboratory periods as well as the assigned homework. Homework assignments and laboratory trials are due at the beginning of the class following the assignments. They are to be placed in an envelope containing the student’s name. The contents of the envelope will be a diskette and a paper copy of the requested Java source code.

Course Requirements: The schedule of activities and topics to be covered each week are outlined below. Each week will begin with responses to questions and a brief review on the previous week’s topics. The first week will begin with administrative announcements and a review of this syllabus.

Grading Policy:

Homework and Laboratory Trials: 1/3

Midterm Exam : 1/3

Final Exam : 1/3

Assignments are due at the beginning of class. Assignments handed in during class lose 5 points, after class 10 points. Late submittals lose 10 points per day including weekends and holidays. Missing a test results in a zero unless a written excuse is presented.

Homework requirements:

Print out a listing of the program. Print out the program intput and output. You may need to do this at various levels of detail. Hand in a labeled disk with a printout. Place the disk in a #10 letter envelope and staple the envelope to the printout.

Topics: (coverage paced will be altered to accomodate the class):

Week 1: Using the AWT - The new Event model

The Graphics Class

Test Patterns

Color Bars

resolution chart

multi-burst test chart

Snell and Wilcox test chart

Interaction

The mouse

The keyboard

The Evt class

building the menu

intercepting menu event

intercepting keyboard events

Week 2: The Model-View Approach

observables and the dialogs boxes

Int Dialog

Float Dialog

File dialogs

The ImageFrame Class

oldPixels

newPixels

menu construction

Week 3: Streams

File input stream

stream tokenizer

closing a file

token flags

writing files

summary for writing files

Save File Example/ set-up main menu bar

Process menu pick - save

Week 4: Digital Image Processing Fundamentals

Overview of Image Processing and its application

Image Storage and Display

image models

cameras video and scanners

Current state of streaming video on the Internet

Problems and solutions

Sampling

Spectra and Spectra

Preview of Image processing

Week 5: The PixelPlane Class

range checking

PixelGrabbers

internal data structures

the ImageStream

the ImageDataStream

Image doubleData

Reading and Writing Images

Reading GIF and JPEG

Writing GIF

Reading PPM

Writing PPM

Week 6: Edge Detection

Roberts, Prewitt, Frei-Chen,

Kirsch, Sobel,

boxcar, pyramid, argyle, Macleod,

derivative of Gaussian, Robinson,

Canny

Laplacian generation, Laplacian of Gaussian

Hat

Week 7: Boundary Processing

XY to Vector Conversion

vector ordering using Dijkstras' algorithm

Edge following and Martellis' algorithm

Divide-and-conquer boundary detection

Range finding via diffraction

Range map to boundary representation

Week 8: Image Enhancement Techniques

Blur

mean, median, unsharp

smoothing binary images by association

local area contrast enhancement

histogram equalization

lowpass filtering

highpass filtering

averaging multiple images

Week 9: Achromatic and Colored Light

Selecting Intensities-Gamma Correction in Java

Chromatic Color

psychophysics

Color models (CIE, RGB, YUV, CMY, HSV, YIQ)

Color coordinate systems

RGB to L*u*v*, L*u*v* to RGB

RGB to L*a*b*, L*a*b* to RGB

RGB to XYZ, XYZ to RGB

RGB to YIQ, YIQ to RGB

RGB to YUV, YUV to RGB

RGB to HSV, HSV to RGB

RGB to HLS, HLS to RGB

Week 10: Thresholding techniques

Global thresholding

multilevel thresholding

variable thresholding

thresholding using image statistics

using mean and standard deviation

using maximization of between-class variance

Week 11: Morphological filtering

set theory

arithmetic operations

boolean operations

erosion and dilation

medial axis transform

skeletonization

Week 12: Warping

scaling

rotation

shear

cutting and pasting

conformal image mapping

warping

Week 13: The Cosine Transform

The Discrete Cosine Transform

The Inverse Discrete Cosine Transform

The Fast Cosine Transform Class

Reading and Writing JPEG Images

Week 14: The InLine MPEG CODEC

Compressed MPEG movies images

decoding MPEG

encoding MPEG

reading MPEG files

writing MPEG files

displaying MPEG files

measuring loss

Implementing in-line Java Decoders

Week 15: The Wavelet Transform

The Discrete Wavelet Transform

The Inverse Discrete Wavelet Transform

The Fast Wavelet Transform Class

Writing a wavelet encoded file

Decoding the wavelet encoded file

Incorporating the decoder with the data

Distribution of wavelet images on the Net.