 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.