SD0015 Image Processing

3 ECTS - 2-0 Duration (T+A)- 0. Semester- 2 National Credit

Information

Unit
Code SD0015
Name Image Processing
Term 2017-2018 Academic Year
Term Fall and Spring
Duration (T+A) 2-0 (T-A) (17 Week)
ECTS 3 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Belirsiz
Label NFE Non-Field Elective Courses (University) UCC University Common Course
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. NAZIM AKSAKER
Course Instructor Prof. Dr. NAZIM AKSAKER (Güz) (A Group) (Ins. in Charge)
Prof. Dr. NAZIM AKSAKER (Bahar) (A Group) (Ins. in Charge)


Course Goal / Objective

In this course, it is aimed to acquire the knowledge and skills of the images used in Astronomy, Remote Sensing and Geographic Information Systems with the help of IDL program processing techniques.

Course Content

Fourier analysis of images, astronomical image analysis, analysis of remote sensing images, use of HUBBLE data archive, use of meteosat data archive, use of Landsat data archive, usage of image data, image, raster and vector data types, command line operations, input / output operations, Use of modis data archive, Image processing techniques in sports encounters, Image processing methods of autonomic tools, Artificial intelligence applications in image processing

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes


Week Plan

Week Topic Preparation Methods
1 Raster, vector data definitions, data formats (FITS, HDF5, GEOTYPE etc.) Literature review on the subject
2 Command-line operations, basic programming logic, algorithms, simple programs. Literature review on the subject
3 Making images visible, analyzing pixels, showing results, getting output. Literature review on the subject
4 Filters (nearest neighbors filter, bin filter etc.), application of interpolations by image. Literature review on the subject
5 Applying the image fast fourier transform. Literature review on the subject
6 Solution of first and second order differential equations by computer programming methods; Finish differences account; Runga-Kutta method; Newton-Raphson method; Bernoulli Equations; Difference method. Literature review on the subject
7 Practical Explanation of Conversion of Photometric Observations to Standard System; Atmospheric Mass, Heliocentric Time Correction, Reduction of Observations in UBV Filter System, First Order Atmospheric Damping Coefficients, Second Order Atmospheric Damping Coefficients, Instrumental Conversion Coefficients (Photometric Scale Factors), Reduction Applications. Conversion to Standard System. Literature review on the subject
8 Downloading and analysis of astronomical images from data archives Literature review on the subject
9 Implementation of techniques for the identification of Pixellar objects Literature review on the subject
10 Determination of learning levels
11 Analyzes of astronomical observations of Hubble, SPITZER, JWST, FITS. Literature review on the subject
12 Analysis of HDF5 format data of meteorological and ground-based satellites. Literature review on the subject
13 Recognition of traffic applications and learning techniques Literature review on the subject
14 Identification of decision making systems and techniques used in sports encounters. Literature review on the subject
15 Application of classification techniques by artificial intelligence learning method in mass data, Examination of methods of producing satellite data. Literature review on the subject


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100

Update Time: 02.01.2018 10:34