EELE 5310: Digital Image Processing Lecture 1 Eng. Ruba A. Salamah Rsalamah @ iugaza.Edu
EELE 5310: Digital Image Processing Lecture 1 Introduction
Transcript of EELE 5310: Digital Image Processing Lecture 1 Introduction
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EELE 5310: Digital Image Processing
Lecture 1
Introduction
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Introduction
Digital image Processing (DIP) course isdesigned to introduce the concepts related todigital images, provide insight into basic digitalimage processing operations and introduce thebasic algorithms used for such purposes.
Textbook: Digital Image Processing, Rafael C.Gonzalez and Richard E. Woods, Second Edition,Prentice-Hall, 2001.
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Prerequisites:
Knowledge of the following three areas:
Linear Algebra.
Signals and Systems.
Programming skills
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Grading Policy
Quizzes & H.W 20%
Midterm Exam 25%
Project 15%
Final Exam 40%
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Outcomes
By the end of this semester ,you will Know basics ofdigital image processing including image acquisition,transformation, compression, enhancement, restoration,analysis, and so on.
Be able to use MATLAB to implement basic imageprocessing algorithms and get familiar with somefunctions provided by MATLAB image processingtoolbox.
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Course outline
Introduction Digital Image Fundamentals Image Enhancement in the Spatial Domain Image Enhancement in the Frequency Domain Image Restoration Image Compression Image Segmentation Image Representation and Description Color image processing
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What is a Digital Image?
A finite array MxNof data values
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What is Image Processing 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
meanings from an image
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Three Types of Processes
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).
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Three Types of Processes cont…
High-level Processes : Processing involves "making sense“ of an ensemble of recognized objects, as in image
analysis, and object recognition.
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Sources of Energy for Image Formation
The principle energy source for images is the EMspectrum
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Some Applications -- Medical Diagnostics
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Some Applications -- MRI
Imaging in Radio Band
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Some Applications -- Industrial Inspection
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Some Applications -- Remote Sensing
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Some Applications -- CBIR
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Some Applications -- Transmitting Images