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Digital Image Processing

What Will Learn?

  • Course Aims
    By the end of the course the students will be able to: • The basic theory and algorithms that are widely used in digital image processing. • Current technologies and issues those are specific to image processing systems. • Developing hands-on experience in using computers to process images. • Developing critical thinking about shortcomings of the state of the art in image processing.
  • Course Goals
  • Industry, Innovation and Infrastructure

Requirements

ECE251s

Description

  • English Description

    Introduction to the theory and applications of 2D signal and image processing: 2D signals and systems analysis, 2D sampling and quantization, 2D signals and image transforms, 2D FIR filter design. Image formation. Image enhancement. Image restoration. Image compression. Image reconstruction from projections. Image compression. Image segmentation. Morphological operations. Super resolution. Wavelets.
  • Arabic Description

    Introduction to the theory and applications of 2D signal and image processing: 2D signals and systems analysis, 2D sampling and quantization, 2D signals and image transforms, 2D FIR filter design. Image formation. Image enhancement. Image restoration. Image compression. Image reconstruction from projections. Image compression. Image segmentation. Morphological operations. Super resolution. Wavelets.
  • Department
    Computer and Systems Engineering
  • Credit Hours
    3
  • Grades
    Total ( 100 ) = Midterm (20) + tr.Student Activities (30 = tr.Industry 0% , tr.Project 10% , tr.Self_learning 0% , tr.Seminar 20% ) + Exam Grade (50)
  • Hours
    Lecture Hours: 3, Tutorial Hours: 1, Lab Hours: 0
  • Required SWL
    125
  • Equivalent ECTS
    5
  • Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Pearson, 2017, Fourth Edition.