To Cover the basic theory and algorithms that are widely used in digital image processing.

To Expose students to current technologies and issues that are specific to image processing systems.

To Develop hands-on experience in using computers to process images.

Familiarize with MATLAB Image Processing Toolbox.

• “Digital Image Processing” by R.C. Gonzalez and R.E. Woods, 3rd edition, Pearson Prentice Hall, 2008

• Additional readings on the class website

Knowledge of the following three areas:

-Linear Algebra.

-Elementary Probability Theory.

-Signals and Systems.

Quizzes 15%

H.W 10%

Attendance 10%

Projects 20%

FinalExam45%

Introduction Digital Image Fundamentals Image Enhancement in the Spatial Domain Image Enhancement in the Frequency

Domain Image Restoration Image Compression Image Segmentation Representation and Description

A finite array of data values

Processing digital images by means of a digital computer.

Image processing typically attempts to accomplish one of three things:

Restoring Images

Enhancing Images

Understanding Images

• Restoration takes a corrupted image and attempts to recreate a clean original

• Enhancement alters an image to makes its meaning clearer to human observers

• Understanding usually attempts to mimic the human visual system in extracting meaning from an image

Low-level Processes :

Involve primitive operations such as image preprocessing to reduce

noise, contrast enhancement, and image sharpening.

A low-level process is characterized by the fact that both its inputs and

outputs are images.

Mid-level Processes:

Involves tasks such as segmentation (partitioning an image into

regions or objects), description of those objects to reduce them to a

form suitable for machine learning , and classification(recognition) of

individual objects.

Its inputs generally are images, but its outputs are attributes extracted

from those images (e.g., edges, contours, and the identity of individual

objects).

High-level Processes :

Processing involves "making sense“ of an

ensemble of recognized objects, as in

image analysis, and, at the far end of the

continuum, performing the cognitive

functions normally associated with vision.

Processing of remote-sensed images via satellite.

Radar, MRI, Ultrasonic image processing.

Noise Reduction.

Character recognition.

Automatic inspection of industrial parts.

Content based image retrieval.

Biometrics.

Target tracking.

The principle energy source for images is the EM spectrum

Other sources include ultrasonic, electronic, and synthetic images.