DATA COMPRESSION

Bruno CARPENTIERI DATA COMPRESSION

0522500077
COMPUTER SCIENCE
EQF7
COMPUTER SCIENCE
2024/2025



YEAR OF DIDACTIC SYSTEM 2016
AUTUMN SEMESTER
CFUHOURSACTIVITY
648LESSONS
ExamDate
APPELLO PROF. CARPENTIERI15/01/2025 - 09:00
APPELLO PROF. CARPENTIERI15/01/2025 - 09:00
Objectives
THE COURSE AIMS TO PROVIDE THE BASIC KNOWLEDGE THAT ALLOWS UNDERSTANDING THE STATE OF THE ART OF THE THEORY AND APPLICATIONS OF DATA COMPRESSION.

KNOWLEDGE AND UNDERSTANDING
THE STUDENT:
- WILL HAVE A STRUCTURED AND ORGANIC VISION OF THE THEORY AND APPLICATIONS OF DIGITAL DATA COMPRESSION THAT WILL INCLUDE THE MAIN IMPLEMENTATION CHOICES AND THE MECHANISMS UNDERLYING THE CHOICE OF A SPECIFIC DATA COMPRESSION ALGORITHM
- WILL HAVE A COMPLETE UNDERSTANDING OF THE BASIC ALGORITHMS FOR LOSSLESS COMPRESSION OF ONE-DIMENSIONAL AND MULTI-DIMENSIONAL DATA
- WILL HAVE A BROAD VISION OF THE BASIC ALGORITHMS FOR LOSSY COMPRESSION OF MULTIDIMENSIONAL DATA
- WILL LEARN HOW THE STANDARDS FOR IMAGE AND VIDEO COMPRESSION WERE CHOSEN
- WILL HAVE A BROAD UNDERSTANDING OF THE STATE OF THE ART AND NEW LINES OF RESEARCH IN THE FIELD OF DATA COMPRESSION
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
THE STUDENT:
- WILL HAVE A STRUCTURED AND ORGANIC VISION OF THE THEORY AND APPLICATIONS OF DIGITAL DATA COMPRESSION THAT WILL INCLUDE THE MAIN IMPLEMENTATION CHOICES AND THE MECHANISMS UNDERLYING THE CHOICE OF A SPECIFIC DATA COMPRESSION ALGORITHM
- WILL HAVE A COMPLETE UNDERSTANDING OF THE BASIC ALGORITHMS FOR LOSSLESS COMPRESSION OF ONE-DIMENSIONAL AND MULTI-DIMENSIONAL DATA
- WILL HAVE A BROAD VISION OF THE BASIC ALGORITHMS FOR LOSSY COMPRESSION OF MULTIDIMENSIONAL DATA
- WILL LEARN HOW THE STANDARDS FOR IMAGE AND VIDEO COMPRESSION WERE CHOSEN
- WILL HAVE A BROAD UNDERSTANDING OF THE STATE OF THE ART AND NEW LINES OF RESEARCH IN THE FIELD OF DATA COMPRESSION
AUTONOMY OF JUDGMENT
THE STUDENT WILL BE ABLE TO:
- DISCERN A PROPOSED PROBLEM WITH SUFFICIENT CLARITY.
- KNOW HOW TO IDENTIFY THE MOST APPROPRIATE METHODS TO SOLVE THE PROBLEM.
- DEFINE THE PROS AND CONS OF THE PROPOSED SOLUTION TO THE PROBLEM.
COMMUNICATIVE SKILLS
THE STUDENT WILL BE ABLE TO:
- EXPLAIN THE OBJECTIVES, THE PROCESS AND THE RESULTS OF THE CHOICES MADE WITH PROPER LANGUAGE
- CLEARLY AND PERSUASIVELY COMMUNICATE CONCEPTS AND SOLUTIONS RELATED TO SOLVING DATA COMPRESSION PROBLEMS
LEARNING ABILITY
THE STUDENT WILL BE ABLE TO:
- APPLY THE KNOWLEDGE ACQUIRED TO CONTEXTS DIFFERENT FROM THOSE PRESENTED DURING THE COURSE
- DEMONSTRATE CONTINUOUS LEARNING ABILITY, STAYING UP TO DATE ON THE LATEST TRENDS RELATED TO DATA COMPRESSION RESEARCH
- CARRY OUT RESEARCH, UNDERSTAND AND INTERPRET COMPLEX TEXTS, OF A SCIENTIFIC OR LITERARY NATURE
- PROCEED WITH THE CONTINUOUS UPDATING OF YOUR KNOWLEDGE, USING THE TECHNICAL AND SCIENTIFIC LITERATURE
Prerequisites
BASICS OF ALGORITHMS AND DATA STRUCTURES.
Contents
THE COURSE CONSISTS OF 48 HOURS OF FRONTAL LESSONS.
THE CONTENTS PROVIDED ARE DESCRIBED BELOW:

PART 1 (24 HOURS)

1) INTRODUCTION TO DATA COMPRESSION

2) LOSSLESS AND LOSSY COMPRESSION

3) INFORMATION THEORY CONCEPTS AND THEORETICAL BASES OF DATA COMPRESSION
(INFORMATION SOURCE, ENTROPY, LIMITS FOR DATA COMPRESSION)

4) SOURCE CODING
(THE ENCODING PROBLEM. HUFFMAN CODING AND ARITHMETIC CODING)

5) STANDARDIZATION

6) COMPRESSION OF ONE-DIMENSIONAL DATA

PART 2 (24 HOURS)
7) COMPRESSION OF IMAGES AND VIDEO

8) DEEPENING OF SOME STANDARD COMPRESSION ALGORITHMS AND DATA:
ARITHMETIC CODING
METHODS BASED ON TEXTUAL SUBSTITUTION
LOSSLESS COMPRESSION OF IMAGES: LOSSLESS JPEG, FELICS, CALIC, THE JPEG-LS STANDARD
THE JPEG STANDARD AND OTHER COMPRESSION STANDARD FOR IMAGES
THE MPEG STANDARD AND OTHER VIDEO COMPRESSION STANDARDS

9) COMPRESSION OF MULTISPECTRAL AND HYPERSPECTRAL IMAGES

10) COMPRESSION OF MULTIDIMENSIONAL DATA

11) COMPRESSION AND SECURITY

12) STATE OF THE ART OF THE RESEARCH IN DATA COMPRESSION
Teaching Methods
THE COURSE INCLUDES A FIRST PART IN WHICH WE EXAMINE THE MAIN APPROACHES TO THE COMPRESSION OF DIGITAL DATA AND THE MOST USED ALGORITHMS.
IN THE SECOND PART STUDENTS SHALL EXPLORE A SPECIFIC TOPIC AS A PROJECT.
THE PROJECT CAN BE THEORETICAL, SUCH AS THE THEORETICAL ANALYSIS OF A NEW COMPRESSION TECHNIQUE, OR PRACTICAL, SUCH AS THE SOFTWARE IMPLEMENTATION AND / OR TESTING OF A PARTICULAR COMPRESSION METHOD, OR BOTH.
Verification of learning
THE EXAM THAT EACH STUDENT MUST TAKE WILL CONSIST OF:

1. A WRITTEN TEST AND AN ORAL TEST FOR THE VERIFICATION OF THE THEORETICAL SKILLS ACQUIRED.
THE WRITTEN TEST WILL PROVIDE FOR A SET OF QUESTIONS DESIGNED TO TEST THE STUDENT'S KNOWLEDGE OF THE MAIN DATA COMPRESSION TECHNIQUES AND OF THE ABILITY TO USE, CONFIGURE AND CHOOSE THE MOST APPROPRIATE METHOD TO DEAL WITH A PROBLEM OF DATA COMPRESSION . 2.DISCUSSIONE AND EVALUATION OF THE PROJECT DONE BY THE STUDENT .
THE LEVEL OF EVALUATION OF THE WRITTEN EXAMS TAKES INTO ACCOUNT THE COMPLETENESS AND ACCURACY OF THE ANSWERS, AS WELL AS THE CLARITY IN THE PRESENTATION.
THE MINIMUM LEVEL OF EVALUATION (18) IS ASSIGNED WHEN THE STUDENT SHOWS AN INCOMPLETE PREPARATION IN THE APPLICATION OF THE METHODS THAT HAVE BEEN STUDIED AND HE HAS A LIMITED UNDERSTANDING OF THE DIFFERENT METHODS STUDIED.
THE MAXIMUM LEVEL (30) IS ASSIGNED WHEN THE STUDENT DEMONSTRATES A COMPLETE AND IN-DEPTH KNOWLEDGE OF THE CONCEPTS AND OF THE DIFFERENT ALGORITHMS PRESENTED DURING THE LECTURES. MOREOVER HE IS ABLE TO SOLVE THE PROPOSED PROBLEMS ARRIVING EFFICIENTLY AND ACCURATELY TO THE SOLUTION AND SHOWS A REMARKABLE ABILITY TO LINK DIFFERENT CONCEPTS TOGETHER.
PRAISE IS GIVEN WHEN THE CANDIDATE WHO DEMONSTRATES A SIGNIFICANT MASTERY OF THE THEORETICAL AND OPERATIONAL CONTENT AND SHOWS HOW TO PRESENT THE TOPICS WITH CONSIDERABLE OWNERSHIP OF LANGUAGE AND AUTONOMOUS PROCESSING SKILLS EVEN IN CONTEXTS DIFFERENT FROM THOSE PROPOSED BY THE TEACHER.
IF, DUE TO THE COVID-19 EPIDEMIC, IT IS NECESSARY TO PROVIDE LESSONS AND EXAMS IN SMART WORKING, THEN WE RESERVE THE POSSIBILITY OF CARRYING OUT ONLY ORAL EXAMS.
Texts
NELSON-GAILLY
"THE DATA COMPRESSION BOOK"
M&T BOOKS

ARTICLES, NOTES AND OTHER MATERIAL PROVIDED BY THE TEACHER.
More Information
E-MAIL: BCARPENTIERI@UNISA.IT
Lessons Timetable

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