Foundations of Multimedia Technologies

1.    Psychophysical fundamentals of the human visual system. The role of rods and cones. Important quantities in radiometry, photometry, colorimetry and their relation. Concept of the luminousity function. CIE RGB and CIE XYZ color spaces.
2.    Concept of brightness adaptation, contrast ratio, and contrast sensitivity as a function of surround luminance level and spatial frequency. The ITU-601 (SD), ITU-709 (HD) and sRGB color spaces. Luminance and chrominance, luma and chroma video components. Concept of chroma subsampling, and chroma subsampling techniques. Quantization of video signals, the ”code 100” problem and the non-linear quantizer characteristics (Opto-electric Transfer function / Gamma function)
3.    SD and HD raster formats and sampling frequencies. UHDTV recommendations and modifications (raster format, color space, etc.)
4.    Fundamentals of signal compression: predictive coding, linear prediction, optimal linear predictor, transform coding, linear algebra basics, optimal transform coding (Karhunen-Loeve Transform), transform coding gain
5.    JPEG encoding: Discrete cosine transform, quantizer matrices, entropy coding (zig-zag ordering, differential coding, run-length encoding, various length coding). Basics of Wavelet transform and wavelet types. JPEG-2000
6.    Video compression: motion estimation and motion compensated prediction. Block matching algorithms and suitable cost functions. MPEG encoding: encoder structure, video layers, frame/picture/block types and MPEG-2 video profiles and levels.
7.    H-264/MPEG-4 AVC encoding: differences from MPEG-2, macroblocks and sub-macroblocks, integer discrete cosine transform and intra prediction. H-265 (HEVC) encoding: comparison with H-274 AVC.
8.    Principles of working and properties of human hearing. Sound pressure, loudness, hearing threshold, masking effects, critical bands, bark-scale, resulting masking curve and the use of all this in psychoacoustic encodings
9.    Tools of audio compression methods: filter banks, MDCT, subband-coding, RLC. Encoding scheme of MPEG 1/2 Part 3 (MP3) and AC-3 (Dolby Digital).
10.    Overview of digital image processing tasks. Two-dimensional and three-dimensional images characteristics, global and local image characteristics. Vector-level and pixel-level description of the images. Images histogram. Histogram equalization.
11.    Axiomatic description of pictures. Scale-space axiomatic system and results. Gaussian smoothing filter and properties. Scale-independent local characteristics. Background enhancement. Connection and geometric relations. Graph-based properties.
12.    Active contours and edge maps. GVF Snake and properties. Harris detector and its applications. Ridge detection. Characteristics Analysis and Testing.
13.    Textures and its borders. Methods of texture enhancement. Statistical textures. Structural textures. Line connections. Houge transformation. Segmentation of noisy shapes.
14.    Summary, overview of exam items
Classroom lectures:
1.    Image processing in MATLAB I.
2.    Image processing in MATLAB II. (video representation, video components and compression)
3.    Qualitative analysis of video compression techniques
4.    Audio processing in MATLAB: MPEG audio encoding
5.    Lossy audio compression techniques
6.    Analysis of image properties in MATLAB
7.    Image transform coding techniques