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Course Description Course Name : Digital Image Proccessing Course Code : UA-504 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Assoc.Prof.Dr. H.MUSTAFA KANDIRMAZ Learning Outcomes of the Course : Knows the basic principles of digital images Makes geometric and algebraic operations on the images Has competence on how to do classifacations Knows how to use package programs Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : To introduce and teach the basic principles of digital images, algebraic and geometric operations on digital images, and how to enhance and classify digital images Course Contents : The course content includes Digital image and its properties, Image display, Raster Data, Vector Data, Spectral and Spatial Enhancement, Supervised and unsupervised classifications, and Package program applications. Language of Instruction : Turkish Work Place : Remote sensing lab.   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction, Basic Definitions search the related subject Lecture and discussion 2 Digitizing images, histogram search the related subject Lecture and discussion 3 Spectral, Temporal, Radiometric and Spatial resolutions, Multispectral images search the related subject Lecture and discussion 4 Image enhancement search the related subject Lecture and discussion 5 Algebraic operations search the related subject Lecture and discussion 6 Geometric operations search the related subject Lecture and discussion 7 Registration search the related subject Lecture and discussion 8 1. Midterm Exam search the related subjects Lecture and discussion 9 Filtering search the related subject Lecture and discussion 10 Unsupervised classification search the related subject Lecture and discussion 11 Supervised classification search the related subject Lecture and discussion 12 The analysis of Principle Components search the related subject Lecture and discussion 13 Applications using package programs-1 search the related subject Lecture and discussion 14 Applications using package programs-1 search the related subject Lecture and discussion 15 Applications using package programs-2 search the related subject Lecture and discussion 16/17 Applications using package programs-3 search the related subject Lecture and discussion   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  An Introduction to Digital Image Processing, Wayne Niblack, Printice Hall International,1986 Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 2 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 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 2 The students identify, describe, formulate and solve problems in engineering, and for this purpose, they are able to select appropriate techniques and apply analytical methods and models. 5 3 The students generate information using remotely sensed data and GIS together with database management skills. 5 4 The students gain knowledge to use current data and methods for multi-disciplinary research. 3 5 The students gain technical competence and skills in using recent GIS and remote sensing software. 3 6 The students have basic information about data collection, management, and analysis through integrating GIS and remote sensing, and are able to solve engineering problems using modern tools and technologies. 4 7 The students develop an understanding of sustainable resource management and planning to meet human needs by taking ecological factors into consideration in light of the current research data. 4 8 The students acquire the necessary knowledge and skills to understand a system, a system component or process for planning purposes, using modern techniques and methods. 4 9 At the end of the programme, the students acquire advanced knowledge on remote sensing and GIS theory. 4 10 The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data. 4 11 The students gain knowledge on temporal, radiometrici, spatial and spectral characteristics of remotely sensed data, as well as optic and active remote sensing systems and their interpretation. 4 12 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. 4 13 The students gain the necessary skills to access information, review the literature, use databases and other sources of information, as well as lifelong learning awareness and the skills to follow scientific and technological developments for personal improvement. 5 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 4 56 Assesment Related Works     Homeworks, Projects, Others 2 10 20     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 16 16 Total Workload: 144 Total Workload / 25 (h): 5.76 ECTS Credit: 6