Infopaket

Digital processing and decoding of images (images)

ДВВ 3.02.01

Вибіркова дисципліна для ОП

First

2023/2024

4 Semester

3

To provide students with advanced knowledge of the theory, methodology and technology of processing digital space photographs. Acquisition of skills in the processing of materials of space photographs, by means of preliminary correction and automated decoding of digital space photographs using modern software.

Full-time form

1) Students should know the basics of remote sensing of the Earth, in particular, the physical basics of electromagnetic radiation, the nature and characteristics of optical radiation, the properties and characteristics of images, the classification of images. 2) Be able to search and download space images from various Internet sources. Visually identify objects in large-scale images based on decipherable features.

"Digital processing and decoding of snapshots (images)" is a discipline focused on mastering the theoretical foundations and modern methods of remote sensing data processing. Basic information about methods of improving spectral and spatial characteristics of images is presented. Automated decryption methods – algorithms for controlled and uncontrolled classification of images.T he discipline consists of two content modules. Within the framework of the first content module, the issues of pre-processing of images with the aim of improving their spectral characteristics are revealed. The content of the levels of processing of DZZ images is revealed. The second module is devoted to the issues of image processing in order to improve their spatial characteristics. Considered: the essence of controlled and uncontrolled classification; formation of the study sample; image transformation algorithms: spectral angle method, minimum distance method, parallelepiped method, maximum likelihood method, Mahalanobis distance method. Binary coding. ISODATA method. The method of K means.

1. Multispectral methods of remote sensing of the Earth in nature management tasks. Under the editorship Lyalka V. I., 2006. 2. Bilous V. V., Bodnar S. P., Kurach T. M., Molochko A. M., Patychenko G. O., Pidlisetska I. O. Remote sensing with the basics of photogrammetry: a tutorial. K.: Kyiv University Publishing and Printing Center, 2011. – 367 p. 3. Burshtynska H. V. Aerospace shooting systems: training. pos., Lviv, 2010. – 292 p. 4. Kokhan S. S., Vostokov A. B., Leontiev O. O. Remote sensing of the Earth. 2010. –300 p. 5. http://man.gov.ua/ua/resource_center/publishing/edition-414

The level of achievement of all planned learning outcomes is determined by the results of practical, independent, modular control tasks and assessment.

The specific weight of learning results in the final assessment, provided that it is mastered at the appropriate level, is as follows: - semester assessment: 1. Modular control work 1: RN 1.1–1.4, 2.1, 2.2 – 10 points. 2. Modular control work 2: RN 1.5–1.6, 2.3 – 10 points. 3. Practical works: RN 1.4 – 4.1 – 30 points. 4. Independent work: grade 1.1 - 1.6 - 10 points. - final evaluation: in the form of credit. The final grade from the educational component, the final form of control for which credit is established, is defined as the sum of grades (points) for all successfully assessed learning outcomes of 60 points and credit of 40 points. Scores below the minimum threshold level are not added to the final score.

Ukrainian