UA504 Digital Image Processing for Remote Sensing

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code UA504
Name Digital Image Processing for Remote Sensing
Term 2022-2023 Academic Year
Term Spring
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. HACI MUSTAFA KANDIRMAZ
Course Instructor
1


Course Goal / Objective

In this course our aim is to give basics of image processing to students

Course Content

In this course informations about types of image, histogram, filtering and classification will be introduced

Course Precondition

none

Resources

Sayısal Görüntü İşleme Rafael C. Gonzales, Richard E. Woods Digital Image Processing Rafael C. Gonzales, Richard E. Woods

Notes

Introduction to Image Processing-Aybars UĞUR


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Knows properties of electromagnetic spectrum
LO02 Defines image and image formation
LO03 knows Image enhancement
LO04 Gets basics of image filtering
LO05 knows the basics of classification and classification types


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal At the end of the programme, the students acquire advanced knowledge on remote sensing and GIS theory 3
PLO02 Bilgi - Kuramsal, Olgusal The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data 4
PLO03 Bilgi - Kuramsal, Olgusal The students generate information using remotely sensed data and GIS together with database management skills. 3
PLO04 Bilgi - Kuramsal, Olgusal The students develop the necessary skills for selecting and using appropriate techniques and tools for engineering practices, using information technologies effectively, and collecting, analysing and interpreting data. 2
PLO05 Bilgi - Kuramsal, Olgusal The students gain knowledge to use current data and methods for multi-disciplinary research 3
PLO06 Bilgi - Kuramsal, Olgusal The students gain technical competence and skills in using recent GIS and remote sensing software 3
PLO07 Bilgi - Kuramsal, Olgusal The students acquire knowledge on potential practical fields of use of remotely sensed data, and use their theoretical and practical knowledge for problem solution in the related professional disciplines. 4
PLO08 Yetkinlikler - Öğrenme Yetkinliği Students will be able to calculate and interpret physical and atmospheric variables by processing the satellite data. 3
PLO09 Yetkinlikler - Öğrenme Yetkinliği Students can generate data for GIS projects using Remote Sensing techniques. 4
PLO10 Bilgi - Kuramsal, Olgusal Gains the ability to analyze and interpret geographic data with GIS techniques 2
PLO11 Bilgi - Kuramsal, Olgusal Gains the ability of problem solving, solving, solution oriented application development
PLO12 Yetkinlikler - Öğrenme Yetkinliği Acquires the ability to acquire, evaluate, record and apply information from satellite data


Week Plan

Week Topic Preparation Methods
1 Electromagnetic radiation Read related documents Öğretim Yöntemleri:
Anlatım
2 Image acquisition Read related documents Öğretim Yöntemleri:
Anlatım
3 Image restoration Read related documents Öğretim Yöntemleri:
Anlatım
4 basic mathamatical operations Read related documents Öğretim Yöntemleri:
Anlatım
5 Image enhancement Read related documents Öğretim Yöntemleri:
Anlatım
6 Geo referencing Read related documents Öğretim Yöntemleri:
Anlatım
7 Geo referencing-continued Read related documents Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Read related documents Ölçme Yöntemleri:
Yazılı Sınav
9 Image filtering Read the related documents Öğretim Yöntemleri:
Anlatım
10 multi-spectral image processing Read related documents Öğretim Yöntemleri:
Anlatım
11 Image Classification Read related documents Öğretim Yöntemleri:
Anlatım
12 Classification models Read related documents Öğretim Yöntemleri:
Anlatım
13 Applications Read related documents Öğretim Yöntemleri:
Anlatım
14 Some applications Read related documents Öğretim Yöntemleri:
Anlatım
15 Some applications -continued Read related documents Öğretim Yöntemleri:
Anlatım
16 Project Applications Read related documents Öğretim Yöntemleri:
Anlatım
17 Term Exams Read related documents Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 30 30
Total Workload (Hour) 154
Total Workload / 25 (h) 6,16
ECTS 6 ECTS

Update Time: 22.11.2022 11:53