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| HRT2018 | Digital Image Processing | 2+0+0 | ECTS:2 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of GEOMATICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Doç. Dr. Volkan YILMAZ | | Co-Lecturer | DOCTOR LECTURER Esra TUNÇ GÖRMÜŞ, | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 4 : | Learning fundemantal definitions and methods for digital image and its formation. | 4,6 | 1,3, | | LO - 6 : | Learning advanced methods for extracting information from digital images. | 4,6 | 1,3, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Matlab image processing toolbox. Image resampling, upsampling and down sampling methods. Histogram processing and contrast enhancement methods. Arithmetical and logical image processing. Spatial image filtering. Noise reduction. Segmentation, image trhresholding and edge detection algorithms. image transformations in frequency domain. Morphological image processing. Wavelet transform and its applications. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction, general description and scope of the course, references | | | Week 2 | Matlab digital image processing toolbox | | | Week 3 | concept of pixel, band and digital image | | | Week 4 | Human vision system. color concept, color models | | | Week 5 | resampling and resizing | | | Week 6 | Histiogram processing, contrast enhancement methods | | | Week 7 | Arithmetical and logical image processing, spatial filtering | | | Week 8 | Blurring and Noise reduction methods | | | Week 9 | Mid-term exam | | | Week 10 | Image segmentation, thresholding and edge detection algorithms | | | Week 11 | Frequency domain, 2-D Fourier transform
| | | Week 12 | Morphological digital image processing | | | Week 13 | Concept of multiresolution and wavelet transform | | | Week 14 | Wavelet transform applications | | | Week 15 | Wavelet transform applications | | | Week 16 | Final Exam | | | |
| 1 | R. C. Gonzalez and E. E. Woods, Digital Image Processing , Prentice Hall, 3rd edition (2007) | | | 2 | Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins-Digital Image Processing Using MATLAB-Gatesmark Publishing (2009) | | | 3 | Mather, P.M. 1987; Computer Processing of Remotely Sensed Images, USA. | | | |
| 1 | Lillesand, T.M , Kiefer, R.W., 1997; Remote Sensing and Image Interpretation, John Wiley Sons, USA. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 1 | 30 | | Homework/Assignment/Term-paper | 12 | | 1 | 20 | | End-of-term exam | 16 | | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 3 | 14 | 42 | | Arasınav için hazırlık | 6 | 6 | 36 | | Arasınav | 1 | 1 | 1 | | Ödev | 3 | 4 | 12 | | Dönem sonu sınavı için hazırlık | 6 | 5 | 30 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 164 |
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