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CONTENTS 1. Introduction 1.1 Course Outline 1 1.2 Introduction ...

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Full Module Title:<br />

DIGITAL IMAGE PROCESSING<br />

Short Module Title: DIGITAL IMAGE PROCESSING<br />

Module Code: 2DPI604 Module Level: 6<br />

Academic credit weighting: 15<br />

Length: 1 semester<br />

School:<br />

Media, Art and Design<br />

Department:<br />

Photographic and Digital Media<br />

Module Leader(s): Liz Allen Extension:4083 e.mail:allene@wmin.ac.uk<br />

Host <strong>Course</strong>:<br />

BSc (Hons) Photography and Digital Imaging<br />

Status:<br />

Option<br />

Pre-requisites:<br />

None<br />

Co-requisites:<br />

None<br />

Assessment: Written Examination 40%<br />

<strong>Course</strong> work 20%<br />

Written Reports from practical assignments 40%<br />

Summary of Module content: Digital Image Processing<br />

The aim of the module is to provide a higher-level understanding of digital image processing and<br />

manipulation techniques and their application. Image enhancement, image restoration, image<br />

segmentation, image analysis, compression, frequency space processing, transformations,<br />

computer vision, image recognition.<br />

Module Aims:<br />

• To gain an understanding of the main classes of digital image processing and<br />

manipulation techniques and their application.<br />

• To extend earlier study of digital imaging systems and the management of image data in<br />

alternative representations.<br />

• To provide students with self-directed and focused practical work, to allow them to gain<br />

experience in the use of image processing to solve specific problems.<br />

• To gain knowledge of practical application of image processing algorithms using MATLAB.<br />

•<br />

Learning Outcomes:<br />

<strong>1.</strong> Be aware of the scope of digital imaging.<br />

2. Understand the main applications and classes of image processing techniques and their<br />

advantages and limitations.<br />

3. Be proficient in the use of MATLAB to write programs for the implementation and testing<br />

of image processing algorithms.<br />

4. Be familiar with methods of image enhancement and restoration in both real and Fourier<br />

spaces.<br />

5. Demonstrate knowledge of fundamental techniques and approaches used in image<br />

segmentation and analysis.<br />

6. Understand and apply image compression correctly to preserve data integrity.<br />

7. Use terminology related to the field correctly.<br />

8. Select appropriate image processing or manipulation algorithms for specific tasks and<br />

understand the relevant implementations.<br />

DPI_Hbook 89 ©University of Westminster

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