• 089837 - MULTIMEDIA SIGNAL PROCESSING 2ND MODULE

The goal of the course is to provide students with advanced knowledge and skills on multimedia signal processing applications, with a specific focus on coding of multimedia objects. This course covers relevant applications of digital signal processing with specific reference to multimedia communication, e.g. audio, image and video coding. Furthermore, the course gives an insight on widely-adopted international coding standards such as MPEG Audio, JPEG and MPEG Video, among others.

• Source coding:
  • Discrete memoryless sources, discrete sources with memory, entropy of a source, uniquely decodable and prefix codes, Shannon’s source coding theorem, Huffman coding, arithmetic coding, run length coding.
• Quantization:
  • Uniform scalar quantization, Lloyd-Max scalar quantization, entropy constrained scalar quantization, rate-distortion theory, vector quantization.
• Predictive coding:
  • Linear predictive coding, DPCM, delta modulation, predictive coding gain.
• Transform coding:
  • Linear transforms, unitary transforms, linear approximation, non-linear approximation, KLT, DCT, transform coding gain, bit allocation, sub-band coding, wavelet transform, 2D transforms.
• A review of Waveform Coding of audio signals:
  • PCM, DPCM, Delta Modulation, ADPCM. Lossless compression techniques.
• Speech coding:
  • Vocal tract modeling, LPC, pitch extraction, voiced/unvoiced detection, analysis by synthesis.
• Audio coding:
  • Fundamentals of psychoacoustics, frequency masking, temporal masking, filter banks (PQMF, MDCT), bit allocation and entropy coding. Coding standards: MPEG-Audio, Advanced Audio Coding (AAC), AC3.
• Image coding:
  • Human visual system, visual redundancy and irrelevancy, lossless and lossy image coding, transform coding and quantization. Coding standards: JPEG.
• Video coding:
  • DPCM, motion estimation, coding of prediction residuals, coding of motion vectors, rate-distortion optimization. Coding standards: MPEG-x, H.264/AVC.
• Other multimedia applications:
  • Multimodal analysis, image intensity pointwise operations, color handling, histogram equalization, morphological processing, feature analysis, matching, registration, forensics.

Students are required to know the basic principles of signal processing and to have basic programming skills.

The assessment will be based on a written exam at the end of the course. The written exam consists of two parts. The first part contains numerical exercises and theoretical questions. This will assign up to 23 points. The second part consists in a programming test. This will assign up to 10 points. 30 cum laude will be assigned when the total score is higher than 31.