MULTIMEDIA AND LABORATORY

Module MULTIMEDIA

Become an expert in multimedia systems concerning images and video, and improve the skills related to multimedia system programming.

General learning objectives in terms of expected learning outcomes.

1. Knowledge and understanding: The aim of the course is to acquire knowledge that will enable the student to understand the theoretical and physical mechanisms behind the signal theory and underlying the human visual system, the formation and processing of video and digital images, enhancing their visual quality.
2. Ability to apply knowledge and understanding: the student will acquire the skills needed to acquire, edit, compress and save images and video signal. 
3. Making judgments: Through examples in the classroom, the student will be put into the condition of understanding whether the solutions offered by him meet a certain degree of quality.
4. Communication skills: The student will acquire the necessary communication skills and technical language skills in the multimedia field.
5. Learning Skills: The aim of the course is to provide the student with the necessary theoretical and practical methodologies to deal with and solve new problems that arise during a work activity. To this end, several topics will be addressed in lesson by involving the student in the search for possible solutions to real problems.

Classroom lessons

Seminars

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

Access to the teaching materials provided by the instructor is available on MS Teams, in the "Multimedia e Laboratorio" Team, code: 28vtwgp.

All communications will take place through the official Telegram channel of the course, so students are requested to join it: https://t.me/+S6Yl1xViNCtJCRmE.

Signals: Introduction to waves, Fourier series, and exercises.

Signals: Types of signals, sampling, Shannon's theorems for sampling and reconstruction, uniform and non-uniform quantization, SQNR (Signal-to-Quantization Noise Ratio), and RMS (Root Mean Square).

Signals: Dithering, types of dithering: random, ordered, error diffusion; Floyd-Steinberg algorithm, Jarvis algorithm.

Signals: Discrete transforms, construction method, Haar transform, Walsh/Hadamard transform, and Fourier transform.

Signals: MATLAB laboratory on the discussed topics.

Digital Video: Aspect Ratio; Resolution; Interlacing; Analog and digital transmission and recording formats.

Digital Video: Analog-Digital Conversion; Part II - Common Registry, Artifact and Drop Errors; Part III - Projections of 3D and 2D space, CAHV model, Matlab lab on the projections, introduction to the most common motion areas.

Digital Video: Stabilization. Digital Stabilization Systems: Motion Vector Integration, Frame Position Smoothing and Kalman Filtering; Examples of image deformation and chromatic stabilization. Matlab Laboratory: motion detection with background subtraction; application example of the Kalman filter; example of video stabilization application using FAST algorithm.

Digital Video: MPEG-1, MPEG-2, MPEG-4, H.264 video formats.

Rust seminars.

Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

The laboratory module focuses on the implementation of the main algorithms for multimedia processing, which are studied in the theoretical module.

The employed programming language are Python and Matlab.

Digital Image Processing, Third Edition, Rafael C. Gonzalez, Richard E. Woods, Ediz. Pearson, Prentice Hall

Audio e multimedia 3 ed., di Lombardo, Valle, Apogeo ISBN: 9788850327621

Video Processing and Communications, Wang, Osternmann, Zhang, Prentice Hall, Pearson Education, ISBN: 0-13-017547-1

In order to take the exam, in accordance with the regulations, it is MANDATORY to register on the Smart Edu portal and on any other platform, as MS Forms, required by the instructor to optimize logistics.

There will be some mid-term exams. A positive result in these exams will exempt students from taking the final exam during the official examination periods

The examination is held in italian language according the rules described in the italian version of this section.

Erasmus students and other non-italian speakers may ask to take an oral exam.

For the assignment of grades for individual assessments, the following criteria are typically followed:

• Fail: The student has not acquired the basic concepts and is unable to complete the exercises.
• 18-23: The student demonstrates a minimal mastery of the fundamental concepts; their ability to present and connect content is modest, and they can solve simple exercises.
• 24-27: The student shows a good grasp of the course content; their ability to present and connect the content is good, and they solve exercises with few errors.
• 28-30 with honors: The student has acquired all course content and can present them comprehensively with a critical perspective; they solve exercises completely and without errors

The assessment of learning may also be conducted remotely if the conditions require it.

Learning will be assessed by completing a software project agreed upon with the instructor.

Students with disabilities and/or learning disorders (DSA) must contact the instructor and the CInAP representative at DMI well in advance of the exam date to inform them of their intention to take the exam with the appropriate compensatory measures.

Questions:

• Explain the origin of the acronym "SECAM" in the analog TV format of the same name, and provide a brief description of how it works.
• What modulation system does SECAM use? Are there any differences compared to the modulation system used in NTSC and PAL?
• Which color space is used in the SECAM analog TV format? What do the three channels of this color space represent, and how are they calculated?
• What are the main advantages and disadvantages of the SECAM analog TV format?

The software projects will focus on course topics, and students may be asked to implement:

• Algorithms for enhancing the quality of multimedia content.
• Algorithms for processing audio/images/videos.
• Algorithms for encoding and compressing multimedia information.
• Algorithms for extracting information related to the semantics of multimedia content.