Lesson Code | Course Name | Class | Credit | Lesson Time | Weekly Lesson Hours (Theoretical) | Weekly Lesson Hours (Practice) | Weekly Class Hours (Laboratory) |
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DGİ 4342 | Digital Image Processing | Үшінші курс | 5 | 150 | 1 | 2 | 2 |
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
1 | Can determine ways of processing, transmitting and storing information. |
2 | Learn image restoration techniques such as noise models, and noise reduction (e.g., spatial filtering, Wiener filtering), etc. |
3 | Learn 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. |
4 | Configures and manages graphics applications and devices to support graphics systems. |
5 | Applies knowledge about the characteristics of graphic devices in establishing interaction with applications. |
6 | Study image segmentation, manipulation, erosion, dilation, compression, filtering, and transformation functions thoroughly. |
Haftalık Konu | Evaluation Method | |
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1 | Introduction to Digital Image Processing: Basics of digital image processing. Advantages and applications. | |
2 | Image Fundamentals: Digital image representation., Image types (binary, grayscale, color), Image enhancement and restoration. | |
3 | Image Enhancement: Histogram equalization Spatial domain methods (e.g., filtering, sharpening, smoothing), Frequency domain methods (e.g., Fourier transform). | |
4 | Image Restoration: Noise models, Noise reduction techniques (e.g., spatial filtering, Wiener filtering). | |
5 | Color Image Processing: Color models, (RGB, CMYK, HSI, etc.) Color transformation and enhancement. | |
6 | Image Segmentation: Thresholding techniques, Edge detection, Region-based segmentation. | |
7 | Morphological Image Processing: Erosion and dilation, Opening and closing, Structuring elements. | |
8 | Image Compression: Lossless and lossy compression, JPEG, JPEG 2000, and other compression standards, Image Filtering and Transformation. | |
9 | Image Filtering and Transformation: Convolution and filtering, Fourier transform and frequency domain filtering. | |
10 | Image Analysis and Feature Extraction: Object recognition, Feature extraction techniques (e.g., shape, texture, and color). | |
11 | Image Registration: Image alignment and registration, Applications in medical imaging and remote sensing. | |
12 | Image Acquisition and Display: Sensors and acquisition systems, Display devices and color management. | |
13 | Image Processing Software and Tools: Introduction to software like MATLAB, OpenCV, or similar tools. | |
14 | Deep learning for image processing, 3D image processing, Image and video coding. | |
15 | Applications and Case Studies: Real-world examples of image processing applications, such as medical imaging, satellite image analysis, and more. |
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Textbook / Material / Recommended Resources | ||
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1 | Компьютерлік графика: Оқу құралы. Алматы: КазҰТУ, 2015. -253 б. Сурет-185. Библиогр. -14 атау. ISBN 978-601-228-736-3 http://rmebrk.kz/book/1138199 | |
2 | Абилдабекова Д. Д. | |
3 | Расторлы және векторлы графика негіздері. Оқу-әдістемелік құрал. [Текст] / Б. Ж. Мамбетова, Ә. Н. Аманов, Ә. Т. Баялы. - Түркістан : Тұран, 2014 | |
4 | Компьютерлік графика: Абилдабекова Д. Д. Оқу құралы. Алматы: КазҰТУ, 2015. -253 б. Сурет-185. Библиогр. -14 атау. ISBN 978-601-228-736-3 | |
5 | Компьютерлік 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 |