Operating Systems
AND SPECIALIZATION TIM
Subject educational effect
Correlation between subject educational effect and educational
effects defined for main field of study and specialization (if
applicable)** Subject objectives*** Programme content*** Teaching tool number***
PEK_W01 (knowledge) S1TMU_W08 C1 Lec1- Lec 5 N1,N2,N3,N5
PEK_W02 S1TMU_W08 C1, C2 Lec 1- Lec 15 N1,N2,N3,N5
PEK_W03 S1TMU_W08 C2 Lec 6- Lec 15 N1,N2,N3,N5
…
PEK_U01 (skills) S1TMU_U07 C3 Lab1 N2,N3,N4
PEK_U02 S1TMU_U07 C3 Lab3-Lab7 N2,N3,N4
PEK_U03 S1TMU_U07 C3 Lab2, Lab3-Lab7 N2,N3,N4
** - enter symbols for main-field-of-study/specialization educational effects *** - from table above
Zał. nr 4 do ZW 64/2012 FACULTY ……… / DEPARTMENT………
SUBJECT CARD
Name in Polish Przetwarzanie obrazów w systemach multimedialnych Name in English Image processing in multimedia systems
Main field of study (if applicable): Telekomunikacja TEL
Specialization (if applicable): Multimedia w telekomuniakcji TMU Level and form of studies: 1st level, full-time
Kind of subject: obligatory Subject code ETES328 Group of courses YES
Lecture Classes Laboratory Project Seminar
Number of hours of organized classes in University (ZZU)
30 15 15
Number of hours of total student workload (CNPS)
60 60 30
Form of crediting Examination crediting with
grade*
crediting with grade* For group of courses mark (X) final course X
Number of ECTS points 5
including number of ECTS points for practical
(P) classes 2 1
including number of ECTS points for direct teacher-student contact (BK) classes
1 1 0.5
*delete as applicable
PREREQUISITES RELATING TO KNOWLEDGE, SKILLS AND OTHER COMPETENCES
1. K1TEL_W14 2. K1TEL_U12
\
SUBJECT OBJECTIVES
C1 To acquire the basic knowledge on digital image processing methods focusing on those used in multimedia systems.
C2 To understand requirements that image processing systems must meet and also to
understand the meaning of algorithms widely used in multimedia systems as well as parameters that characterize the performance.
C3 To acquire skill of implementing basic algorithms of image processing in MATLAB as well as the skill of evaluating such algorithms.
C4 To acquire skill of understanding the requirements related to image processing systems. C5 To acquire skill of choosing appropriate methods of image processing.
SUBJECT EDUCATIONAL EFFECTS
relating to knowledge:
PEK_W01 – has a general knowledge of the formation process, the acquisition and
representation of a color image in the digital system. Familiar with basic relations and parameters ruling that process and understands their influence to the image formation process.
PEK_W02 – familiar with basic concepts of image processing including the concept of the image, convolution, cross-correlation, Fourier transform, two-dimensional filter.
PEK_W03 – has knowledge of basic methods of image processing in digital systems, including expertise in image filtering using FIR filters, median filters, bilateral filters.
PEK_W04 – has a basic knowledge of lossy image compression methods. Familiar with the individual blocks of image processing chain in the JPEG standard and understands their importance. Familiar with image processing methods implemented in the JPEG
standard.
PEK_W05 – has knowledge of basic image analysis tools, including; knowledge on properties of the two-dimensional Fourier transform and knowledge on basic tools for statistical image analysis. Understands the importance of basic parameters of the image.
relating to skills:
PEK_U01 – can use simulation software (MATLAB) to the extent necessary to implement the basic image processing algorithms.
PEK_U02 – can prepare appropriate procedures and data to test the operational correctness of the implemented algorithms.
PEK_U03 – can implement the basic algorithms of digital image processing.
PEK_U04 – can design a simple image acquisition system using ready-to-use components or items i.e. camera, computer, software.
PEK_U05 – can prepare the data and procedures used to evaluate the quality and performance of the implemented algorithms
…
relating to social competences: PEK_K01
PEK_K02
PROGRAMME CONTENT
Form of classes – lecture Number of hours Lec
1
Introduction to digital image processing. Description of basic image processing chain. Examples of systems and applications.
222
Lec 2
The image formation process. The importance of the basic elements of a typical camera. CCD and CMOS image sensors. Color image acquisition techniques. Representation of images in digital systems.
Lec 3
The basic operations performed on images, including: sampling, quantization, convolution, cross-correlation
4
Lec 4
Image transforms, including: Fourier transform, discrete cosine transform. 4
Lec 5
Basic methods of image filtering, including: FIR filters, bilateral filters, median filters, homomorphic filters
8
Lec 6
Selected methods of image analysis, including: edge detection, histogram modeling
24
Lec 7
Selected image coding methods, including: JPEG standard 22
Total hours 30
Form of classes – laboratory Number of hours
Lab 1
Preparation for image processing in MATLAB. Getting to know the basic commands for reading and writing images to disk, the command to display the images. To know the ways of representation of different types of images
2
Lab 2
Observation of the effects of sampling and quantization of images. 1 Lab
3
Development of individual codes implementing convolution and cross-correlation. Preparation of the test images. Testing of the codes using prepared images. Evaluation of the obtained results
2
Lab 4
The use of Fourier Transforms for image analysis, including the preparation of the relevant test images, learn how to use procedures of forward and inverse Fast Fourier Transforms (FFT) in MATLAB software. Running tests on sample images. Property analysis of Fourier transform and evaluation of the use of Fourier transform as a tool for image analysis.\
2
Lab 5
Development of individual codes implementing simple FIR filter, bilateral filter, median filter. Preparation of the test images. Testing of the codes with the use of prepared images. Validation of codes developed and the speed of the filter as a function of its row. Evaluation of filters for their effectiveness in the process of denoising the image
3
Lab 6
The use of Discrete Cosine Transform in the coding (compression) images, including: preparation of relevant test images, learn how to use procedure of forward and inverse DCT available in MATLAB.
Running tests on example images. Property analysis of the DCT and the assessment of its possible use as a tool for image compression
1
Lab 7
Development of individual codes implementing simple edge detectors. Preparation of the test images. Running tests on prepared images. Validation of the developed codes. Evaluation of detectors designed to search specific features of the image. Comparison of the performance of the codes developed with the procedures existing in MATLAB.
2
Lab 8
Development of individual codes implementing simple algorithms for evaluating basic image statistics: mean value, variance, histogram.