Computational Aesthetics
This lecture overviews Computational Aesthetics that has many applications in visual arts and computer graphics. It covers the following topics in detail: Neuroaesthetics. Computational Aesthetics. Critical problems in aesthetics. Connection with Deep Learning. Facial Attractiveness Prediction Paintings – Generative art.
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Image Quality
This lecture overviews Image Quality that has many applications in image filtering, processing, transmission, streaming and TV. It covers the following topics in detail: Image Quality Assessment Methods, Subjective Quality Assessment Methods, Objective Quality Assessment, Image Quality Metrics, Full reference Quality Assessment-Metrics, Experimental Results, Reduced reference Quality Assessment, No reference Quality Assessment-Metrics, Error Sensitivity, Factors of image quality in cameras.
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Colour Theory
This lecture overviews Colour Theory that has many applications in digital image/video processing and analysis, multimedia sites and in digital TV. It covers the following topics in detail: Light wavelength, Human Visual System (rods, cones), color opponency HVS models. Colour cameras, Bayer filters, multichannel/hyperspectral/infrared/ultraviolet images.Brightness/Chromaticity, RGB/XYZ/UCS/UVW/Lab colour coordinate systems. Colour TV, YIQ/YCbCr color coordinate systems, CMYK colour image printing. Colour hue, saturation, luminance and HLS/HSV color coordinate systems.
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Image Perception
This lecture overviews Image Perception. This is very important to understand image quality issues and develop many appropriate image processing operations. It covers the following topics in detail: Human Vision Modelling, Weber ratio, Mach Phenomenon. Mathematical neuron model. HVS has band-pass frequency characteristics, Laplacian-of-Gaussian retina modelling. V1 visual cortex and Gabor functions. Spatial HVS models, Angular Spatial Frequency, Kelly experiments, Saccadic eye motion, HVS Contrast sensitivity. Gestalt theory. Visual illusions.
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Human Visual System
This lecture overviews the Human Visual System that has many applications in understanding image perception and image quality issues. It covers the following topics in detail: Human Visual System (eyes and visual pathway, stereo vision). Retina (rods, cones, ganglion receptive fields, colour theory). Visual Pathway (optic nerves, optic chiasma, optic tract, Lateral Geniculate Nucleus, Corpus Callosum, optic radiation). Visual Cortex: V1 (primary visual cortex) and V2-V6 visual areas. Visual defects, e.g., refractive errors, colour related visual defects, Form visual defects, Motion visual defects.
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Digital Image Formation
This lecture overviews Image Formation, which is of primary importance in ensuring image quality and enabling image processing. It covers the following topics in detail: Light reflection models. Camera structure and models, e.g., Pinhole Camera. Camera Lenses. Image Formation Models. Optical sensors, e.g., CCDs. Image scanners. Image acquisition issues: gamma correction, while balance. Image quantisation and digitisation. Probabilistic Image Description. Image noise and noise generators.
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