Information
Code | UA504 |
Name | Digital Image Processing for Remote Sensing |
Term | 2023-2024 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 |