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Information
| Code | UA004 |
| Name | Image Processing Techniques in IDL-2 |
| Term | 2024-2025 Academic Year |
| Semester | . Semester |
| 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. NAZIM AKSAKER |
Course Goal / Objective
In this course, the techniques used in Astronomy, Remote Sensing and Geographical Information Systems are aimed to gain knowledge and skills related to the processing techniques of IDL program.
Course Content
IDL and image processing techniques will be explained.
Course Precondition
None
Resources
Lecture Notes
Notes
Lecture Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Apply by programming with algorithm. |
| LO02 | Establishes a connection between input / output processes |
| LO03 | Applies image filtering techniques |
| LO04 | Implements fourier analysis to images |
| LO05 | Distinguish astronomical images and apply basic image processing methods. |
| LO06 | Apply trained / uneducated classification techniques. |
| LO07 | Recognize remote sensing satellites, |
| LO08 | Recognize the astronomical satellites and use their archives. |
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 | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | The students generate information using remotely sensed data and GIS together with database management skills. | |
| 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. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | The students gain knowledge to use current data and methods for multi-disciplinary research | 4 |
| PLO06 | Bilgi - Kuramsal, Olgusal | The students gain technical competence and skills in using recent GIS and remote sensing software | |
| 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. | 3 |
| PLO08 | Yetkinlikler - Öğrenme Yetkinliği | Students will be able to calculate and interpret physical and atmospheric variables by processing the satellite data. | |
| 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 | 5 |
| 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 | What is image, Raster, vector data definitions, data formats (FITS, HDF5, GEOTIF etc.) | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 2 | Command Line operations, basic programming logic, algorithm, simple programs | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 3 | Visualization of images, pixel analysis, showing the results, output. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 4 | Visualization of images, pixel analysis, showing the results. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 5 | Filtering (closest neighborhood filter, splash filter), application of interpolations to images. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 6 | Visualization of images, px analysis, showing the results, output. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 7 | Application of Converting Tometric Observations to Standard System. As a Preparation; JD-Date, JD Transformation, Mean and Visible Star Times, Air Mass, HeliocentricTime Correction, Reduction of Observations in UBV Filter System, First-Order Atmospheric Damping Coefficients, Second-Order Atmospheric Damping Coefficients, Instrumental Conversion Coefficients (Photometric ScaleFactors), Reduction Applications. Conversion to Standard System | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
|
| 9 | Applying techniques to identify objects from pixels | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 10 | Analysis of meteorological and ground-based satellites in HDF5 format. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 11 | Learns to manipulate FITS data format. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 12 | Learns to manipulate Fits data format. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 13 | Analysis of the astronomical satellites of Hubble, SPITZER, JWST. | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 14 | Analysis of the data in the astronomical satellites Hst | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 15 | Analysis of the data in the astronomical satellites imece | no preliminary preparation. | Öğretim Yöntemleri: Anlatım |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev, Yazılı Sınav |
|
| 17 | Term Exams | Ölçme Yöntemleri: Ödev, 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 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||