On the 5 November PhD student Ed Fry will present a research seminarentitled: The Importance of Contextual Contrast Sensitivity and Contrast Discrimination Functions in Image Quality at the Harrow Campus, Room A 6.01.

Contextual contrast sensitivity and contrast discrimination functions (cCSF and cVPF) will be first reviewed in this talk, along with details on work undertaken within Computational Vision and Imaging Technology (CVIT) in the last four years on their derivation from real complex scenes and their modelling. Further, research on optimal luminance contrast weighting-function for image quality optimisation will be presented.

Traditionally measured contrast sensitivity functions (CSFs), have been often used as weighting-functions in image quality and difference metrics. Such weightings have been shown to result in increased sharpness and perceived quality of test images. Ed Fry suggests contextual CSFs (cCSFs) and contextual discrimination functions (cVPFs) should provide bases for further improvement, since these are directly measured from pictorial scenes, modeling threshold and suprathreshold sensitivities within the context of complex masking information. Image quality assessment is understood to require detection and discrimination of masked signals, making contextual sensitivity and discrimination functions directly relevant.

During the investigation presented in the seminar, test images were weighted with a traditional CSF, cCSF, cVPF and a constant function.

Controlled mutations of these functions were also applied as weighting-functions, seeking the optimal spatial frequency band weighting for quality optimization. Image quality, sharpness and naturalness were then assessed in two-alternative forced- choice psychophysical tests.

Ed also showed that maximal quality for test images, results from cCSFs and cVPFs, mutated to boost contrast in the higher visible frequencies.