The course and the examination are 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
MULTIMEDIA AND LABORATORYModule LABORATORY
Academic Year 2023/2024 - Teacher: FILIPPO STANCOExpected Learning Outcomes
Become an expert in multimedia systems: images, audio and video.
General learning objectives in terms of expected learning outcomes.
Knowledge and understanding: The aim 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 sound, video and digital images, enhancing the visual quality of digital images and audio quality.
Ability to apply knowledge and understanding: the student will acquire the skills needed to acquire, edit, compress and save a viedeo audio signal. Particularly a part of the course will be related to the study of Matlab software to apply such theoretical knowledge.
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
Laboratory lessons
Required Prerequisites
Pass the course "Interaction and Multimedia" held at the BSc.
Attendance of Lessons
attendance is strongly recommended
Detailed Course Content
Evaluating the quality of an image. Objective and subjective criteria. PSNR, SSIM, Delta E in CIE L* a* b*.
Raster and vector image formats. Image formats: BMP, PNG, TIFF, GIF. Compression and Coding: Huffman, Golomb, Arithmetic.
LZW, differential, RLE, code-based encodings, based on the symbols on the bit plane. Encrypt using the transform.
Transformed Haar, Fourier, DCT.
The mathematical morphology applied to the images.
The mathematical morphology applied to the images in gray scale.
restoring images. Noise patterns
Arithmetic, geometric, harmonic and harmonic media filters. Median filter, minimum, maximum, midpoint, alpha-trimmed. Adaptive Filters. Periodic noise. Removing noise in the frequency domain. Notch filter. Wiener filter.
Filtering in Spatial Domain. Edge detector. Canny Algorithm. Filtering in the frequency domain. Stress filtering. Homomorphic filtering. Hough transformed.
Segmenting Images
Examples of coding using Matlab
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.
Learning assessment may also be carried out on line, should the conditions require it.
Textbook Information
Digital Image Processing, Third Edition, Rafael C. Gonzalez, Richard E. Woods, Ediz. Pearson, Prentice Hall
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | Restauro e ricostruzione di immagini | Capitolo 5 di "Elaborazione delle Immagini Digitali" |
| 2 | Morfologia applicata alle immagini digitali | Capitolo 9 di "Elaborazione delle immagini digitali" |
| 3 | La Segmentazione di immagini | Capitolo 10 di "Elaborazione delle immagini digitali" |
| 4 | Codifiche, formati di immagini | Capitolo 8 di "Elaborazione delle immagini digitali" |
Learning Assessment
Learning Assessment Procedures
Examples of frequently asked questions and / or exercises
Random noise in images:
What is random noise in images? What can it be introduced by?
Let P be a probability distribution with the law P(x)=0.10 for x=0; P(x)=0.25 for x=255; P(x)=0 otherwise. Where x is an 8-bit (integer) luminance value. What is the name of the noise that follows this probability distribution? Discuss the significance of the distribution described.
What is the contraharmonic averaging filter? How is it defined?
Can the contraharmonic averaging filter be used to attenuate the aforementioned P-distribution noise? If yes, explain how. If not, propose another type of filtering.
Morphological operators:
What is the structuring element in mathematical morphology applied to images?
What is the Bottom-hat morphological operator used for?
The Closure operator is used in the definition of the Bottom-hat operation. How is this Closing operation defined? What are its effects?
Indicate at least one mathematical property of the Closure operator.