HUMAN INTERACTION and MULTIMEDIA and Lab M - ZModule HUMAN INTERACTION and MULTIMEDIA
Academic Year 2023/2024 - Teacher: DARIO ALLEGRAExpected Learning Outcomes
General learning objectives in terms of expected learning outcomes.
Knowledge and understanding: The purpose of the course is to acquire knowledge that will enable the student to understand the theoretical and physical mechanisms underlying the human visual system, the formation and processing of digital images, of the improvement of the visual quality of digital images. Ability to apply knowledge and understanding: the student will acquire the skills needed to acquire, edit, compress, and save a digital image.
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.
Communication skills: The student will acquire the necessary communication skills and technical language skills in the multimedia field.
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.
Course Structure
Classroom lessons
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.
Attendance of Lessons
Detailed Course Content
Introduction to digital images
Image formation in the human eye
Thin lens equation
Optical illusions
Digital sensors
The Bayer pattern
Color interpolation
Raster images and vector images
Representation of raster images
Campinamento
quantization
Aliasing
Digital Image Resolution
Interpolation replication, bilinear and bicubic
PSNR
Color
The RGB, CMY, HSV, Munsell, YUV, YCbCr
Indexed images and palettes
Reindexing
The histogram of an image
Punctual operations and LUTs
Bit-planes
Linear and invariant operators for translation
Noise reduction
Edge detection
Space domain
Frequency domain
Fourier transform
The convolution and convolution theorem
Lossy and lossless compression
Shannon's theorem for compression
Huffman Encoding
The Jpeg standard
Textbook Information
Digital Image Processing, (3rd Edition) Rafael C. Gonzalez, Richard E. Woods, Ediz. Pearson, Prentice Hall
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | La percezione visiva, Acquisizione delle immagini, campionamento e quantizzazione, strumenti matematici usati nella elaborazione delle immagini | Capitolo 2 di "Elaborazione delle Immagini Digitali" |
| 2 | Istogrammi, filtraggi spaziali, Smoothing | Capitolo 3 di "Elaborazione delle Immagini Digitali" |
| 3 | Filtraggio nel dominio delle frequenza, trasformata di Fourier, Filtraggi nel dominio della frequenza | Capitolo 4 di "Elaborazione delle Immagini Digitali" |
| 4 | Rumore, filtraggio spaziale | Capitolo 5 di "Elaborazione delle Immagini Digitali" |
| 5 | Spazi colore | Capitolo 6 di "Elaborazione delle Immagini Digitali" |
| 6 | Compressione delle immagini | Fondamenti di Image Processing |
Learning Assessment
Learning Assessment Procedures
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
Examples of frequently asked questions and / or exercises
- Is the "power" operator punctual, local, or global? What does this mean? Typically, does this operator brighten or darken the image? Apply the power ^2 operator to the matrix provided below. Finally, linearly normalize the resulting matrix between 0 and 255.
56 | 45 | 11 |
67 | 100 | 232 |
0 | 129 | 50 |
- What are the fundamental characteristics of Huffman coding? Construct the Huffman coding for the symbols that make up the string "exam for exam."