1. COURSE TITLE Multimedia Signal Processing I: visual signals Course number Course area Course type Course level. 1.5.

Size: px

Start display at page:

Download "1. COURSE TITLE Multimedia Signal Processing I: visual signals Course number Course area Course type Course level. 1.5."

Daniel Bishop
5 years ago
Views:

1 1. COURSE TITLE Multimedia Signal Processing I: visual signals 1.1. Course number Course area Computer Science Engineering 1.3. Course type Elective course 1.4. Course level Graduate 1.5. Year 4º 1.6. Semester 1º 1.7. Credit allotment Prerequisites Multimedia signal Processing I: visual signals belongs to Area 6: Digital Signal Processing, from the elective course module of the Degree in Computer Science and Engineering. The Area 6 is composed of three semester courses: two of them focused on the processing of multimedia signals, Multimedia Signal Processing I: visual signals (first semester) and Multimedia Signal Processing II: audio signals (second semester). Then, 1 de 7

2 a third one oriented to application-level, Development of Multimedia and Multimodal Applications, which is taught during the second semester. For this course, it is required to have a general knowledge of programming and the most common mathematical tools. To facilitate the assimilation and learning of the course contents, it is recommended to perform a critical reading of the references listed in the course bibliography, the frequent use of the material available at the Moodle platform ( and the search of related contents in the Web Minimum attendance requirement No minimum attendance is required for this course Faculty data to all addresses below. Theory: Dr. Juan Carlos San Miguel Avedillo Departamento de Tecnología Electrónica y de las Comunicaciones Escuela Politécnica Superior Office - Módulo: C-205 Edificio C 2ª Planta Telephone: juancarlos.sanmiguel Web: Practice: Dr. Juan Carlos San Miguel Avedillo Departamento de Tecnología Electrónica y de las Comunicaciones Escuela Politécnica Superior Office - Módulo: C-205 Edificio C 2ª Planta Telephone: juancarlos.sanmiguel Web: 2 de 7

3 1.11. Course objectives The main objective of this course is to describe the fundamentals of the processing of digital images (multimedia signals related to the visual field). The course assumes that students have a solid knowledge of programming and the most common mathematical tools. This course is structured into seven units. First, an introduction to the analysis of images is presented in which the linear system theory is briefly reviewed for the onedimensional case. Then, the second unit describes its extension to the processing of digital images in a generic aspect: frequency analysis, sampling, interpolation and quantification. After that, the third, fourth and fifth units cover the most common operations of digital image processing at, respectively, point, local and global level. The sixth unit describes basic applications of the previously described operators. Finally, the last unit presents generic aspects of color and light and gives an overview of capture and display technologies. In parallel with the course contents, a number of practice lessons have been programmed to illustrate and experiment with the presented concepts in the theoretical sessions. In particular, nine practical sessions have designed for learning the programming tools and the main algorithms of image processing. Then, a final project (that comprises four practical sessions) is proposed to demonstrate the acquired knowledge in the course. Such sessions will be done in pairs making use of the Image Processing Toolbox of the MatLab software package. The skills provided by this course (that do not form part of the compulsory ones specified in the syllabus of the Computer Science and Engineering degree) are: Understanding of the fundamentals of visual content analysis allowing to develop algorithms for digital image and video processing In particular, at the end of each unit, the student should be capable of: UNIT BY UNIT SPECIFIC OBJECTIVES UNIT 1.- Introduction 1.1. Understanding the different types of available visual signals 1.2. Understand the fundamentals of the one-dimensional signal analysis 1.4 Basic use of the MatLab software package for signal processing 1.5 Use of scripts and functions in MatLab UNIT 2.- Fundamentals of multidimensional signals and systems processing 2.1. Understand the basics for acquisition of images 2.2. Understand the basics for the composition and creation of images 2.3. Generation and representation of images from analytical expressions Perform basic operations with images 3 de 7

4 UNIT 3.- Point operators 3.1. Understand and use the image histogram concept 3.2. Understand and use the algorithms for modifying an image through histograms 3.3. Understand and use the algorithms for modifying an image through binary operations 3.4. Design of algorithms based on local operators 3.5. Computation of image histograms and analysis of their utility Implementation of the most common point operators to study their effect on real and 3.6. synthetic images UNIT 4.- Local operators 4.1 Understand and use of the frequency analysis of images 4.2 Understand and use the spatial operators for smoothing, enhancing and edge detection on images 4.3 Understand the fundamentals of mathematical morphology and design algorithms based on the basic operations (dilation, erosion, ) 4.4 Design algorithms based on local operators 4.5 Practical use of the Fourier transform for images 4.6 Practical use of the basic operators for frequency filtering, sampling and interpolation of images 4.7 Practical use of the basic morphological operators TEMA 5.- Global operators 5.1 Understand the fundamentals of the global transformation of images 5.2 Understand the properties of the most common transformations applied to image processing 5.3 Design algorithms based on global operators 5.4 Implementation of the most common image transforms 5.5 Practical study of the properties of the implemented transforms TEMA 6.- Applications Understand and use of the main algorithms for keypoint extraction and 6.1. characterization 6.2. Understand and use of the main algorithms for edge extraction 6.3. Understand and use of the main algorithms for region analysis 6.4. Design and implementation of algorithms based on point, local and global operators 6.5. Write a report related with image processing 6.6. Presentation of a project related with image processing TEMA 7.- Introduction to visual perception 7.1. Understand the basics for color management 7.2 Understand the current status of capture and display technologies for image/video 4 de 7

5 1.12. Course contents 1. Introduction 1.1. Introduction to the processing of visual signals 1.2. Introduction to the processing of one-dimensional signals PRACTICAL LESSON 0: Introduction to MatLab (two sessions) 2. The digital image 2.1. Introduction 2.2. Frequency representation of images 2.3. Sampling of multidimensional signals Lattice theory Sampling theory 2.4. Image sampling 2.5. Image quantification 2.6. Decimation and interpolation of images PRACTICAL LESSON 1: Images in MatLab (one session) 3. Point operators 3.1. Introduction 3.2. Histogram modeling 3.3. Level modification 3.4. Operational aspects 3.5. Binary processing PRACTICAL LESSON 2: Point operations (two sessions) 4. Local operators 4.1. Introduction 4.2. LSI operators Impulse and frequency response Operational aspects Design of frequency mask Smoothing Contour enhancement Detection and localization of edges 4.3. Geometrical operators Types D operators D/3D operators 4.4. Morphological operators Geometrical analysis for image processing Dilation and erosion Morphological gradient 5 de 7

6 Opening and closing Filtering by reconstruction PRACTICAL LESSON 3: LSI systems (one session) PRACTICAL LESSON 4: Local operators I (one session) PRACTICAL LESSON 5: Local operators II (one session) 5. Global operators 5.1. Introduction 5.2. One-dimensional discrete lineal transforms Presentation Matrix representation Properties DFT: Discrete Fourier Transform FFT: Fast Fourier Transform 5.3. Two-dimensional discrete lineal transforms Presentation DFT: Discrete Fourier Transform DCT: Discrete Cosine Transform DST: Discrete Sine Transform Others Transforms Comparison PRACTICAL LESSON 6: Global operators (one session) 6. Applications 6.1. Introduction 6.2. Extraction and description of points/corners Harris SUSAN FAST SIFT Comparison 6.3. Edge extraction Canny Hough Transform Generalized Hough transform Contour tracking Active contours 6.4. Region extraction Thresholding Connected components Region growing and partition PRACTICAL LESSON 7: Project (four sessions) 7. Fundamentals of visual perception 7.1. Image formation 6 de 7

7 Light Luminance and color Brightness Contrast Gamma correction SVH response Quality criteria 7.2. Color management Tri-croma theory (Trichromacy) Chromaticity Color temperature and white balance 7.3. Capture technologies 7.4. Display technologies Course bibliography Note: This course does not strictly follow any particular book (only selected chapters). The slides provided to the students represent the reference material of the course. Basic: A.K. Jain, "Fundamentals of Digital Image Processing", Prentice Hall, R.C. Gonzalez, R.E: Woods, "Digital Image Processing", 3ª Ed, Prentice Hall, (2ª Ed, 2002) Y. Wang, Video Processing and Communications, Prentice Hall, Additional: C. Solomon, "Fundamentals of digital image processing a practical approach with examples in Matlab", John Wiley, 2011 W. Pratt, "Digital image processing PIKS", 4ª Ed., John Wiley & Sons, (3ª Ed online) B. Jahne, "Digital Image Processing", 6ª Ed., Springer-Verlag, 2005 For practical sessions: R. C. Gonzalez, R. E. Woods, "Digital Image Processing using Matlab", Prentice-Hall, U. Qidwai and C.H. Chen, "Digital image processing an algorithmic approach with MATLAB", Chapman & Hall, 2009 The electronic material of the course (slides, exercises, documents for practical sessions, past tests, etc.) are published in the TSSMM1 section of the Moodle platform ( 7 de 7

Digital Image Processing

Digital Image Processing Third Edition Rafael C. Gonzalez University of Tennessee Richard E. Woods MedData Interactive PEARSON Prentice Hall Pearson Education International Contents Preface xv Acknowledgments