Information Systems
Lesson Code Course Name Class Credit Lesson Time Weekly Lesson Hours (Theoretical) Weekly Lesson Hours (Practice) Weekly Class Hours (Laboratory)
DGİ 4342 Digital Image Processing Үшінші курс 5 150 1 2 2
Course Descriptions
Turkish
PhD, A.N. Amanov

Discipline allows you to study digital image processing packages. Discipline will allow you to explore the methods of presenting graphic images, color systems in computer graphics, graphic file formats, the basics of digital image processing, and applying digital image processing packages, depending on the task.

Basics of GIS technologies

Computer graphics and their application

1Can determine ways of processing, transmitting, and storing information.
2Learn image restoration techniques such as noise models, and noise reduction (e.g., spatial filtering, Wiener filtering), etc.
3Learn techniques for histogram smoothing in the spatial domain, including filtering, sharpening, and smoothing. Also, master image enhancement techniques such as those in the frequency domain, like the Fourier transform.
4Configures and manages graphics applications and devices to support graphics systems.
5Applies knowledge about the characteristics of graphic devices in establishing interaction with applications.
6Study image segmentation, manipulation, erosion, dilation, compression, filtering, and transformation functions thoroughly.
Haftalık KonuEvaluation Method
1Introduction to Digital Image Processing: Basics of digital image processing. Advantages and applications.
2Image Fundamentals: Digital image representation., Image types (binary, grayscale, color), Image enhancement and restoration.
3Image Enhancement: Histogram equalization Spatial domain methods (e.g., filtering, sharpening, smoothing), Frequency domain methods (e.g., Fourier transform).
4Image Restoration: Noise models, Noise reduction techniques (e.g., spatial filtering, Wiener filtering).
5Color Image Processing: Color models, (RGB, CMYK, HSI, etc.) Color transformation and enhancement.
6Image Segmentation: Thresholding techniques, Edge detection, Region-based segmentation.
7Morphological Image Processing: Erosion and dilation, Opening and closing, Structuring elements.
8Image Compression: Lossless and lossy compression, JPEG, JPEG 2000, and other compression standards, Image Filtering and Transformation.
9Image Filtering and Transformation: Convolution and filtering, Fourier transform and frequency domain filtering.
10Image Analysis and Feature Extraction: Object recognition, Feature extraction techniques (e.g., shape, texture, and color).
11Image Registration: Image alignment and registration, Applications in medical imaging and remote sensing.
12Image Acquisition and Display: Sensors and acquisition systems, Display devices and color management.
13Image Processing Software and Tools: Introduction to software like MATLAB, OpenCV, or similar tools.
14Deep learning for image processing, 3D image processing, Image and video coding.
15Applications and Case Studies: Real-world examples of image processing applications, such as medical imaging, satellite image analysis, and more.
Relationship between the Curriculum and Learning Outcomes
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Textbook / Material / Recommended Resources
1Компьютерлік графика: Оқу құралы. Алматы: КазҰТУ, 2015. -253 б. Сурет-185. Библиогр. -14 атау. ISBN 978-601-228-736-3 http://rmebrk.kz/book/1138199
2Расторлы және векторлы графика негіздері. Оқу-әдістемелік құрал. [Текст] / Б. Ж. Мамбетова, Ә. Н. Аманов, Ә. Т. Баялы. - Түркістан : Тұран, 2014
3Компьютерлік графика: Абилдабекова Д. Д. Оқу құралы. Алматы: КазҰТУ, 2015. -253 б. Сурет-185. Библиогр. -14 атау. ISBN 978-601-228-736-3
4Компьютерлік графиканың теорияльщ негіздері. Компьютерлік графикадан орындалатын зертханалық жұмыстарға әдітемелік нұсқау Ж. М. Есмұхан, Ә. Құспеков, E. Е. Мәсімбаев- Алматы: К,. И. Сәтбаев атындагы ҚазҰТУ, 2015. 1-416. http://rmebrk.kz/book/1138154