Computational Vision and Imaging Technology Research Group

Research projects

Optical image quality metrication employing human visual system modeling

Edward Fry is a PhD student specialising in the production of Optical Image Quality Metrics, which incorporate current human visual sensitivity models.

E: [email protected]

Project Overview

This project, which began in September 2015, proposes to create image quality metrics for use in the engineering of optical systems, including image capture devices. 

The proposed metrics will develop upon existing reference-free image quality metrication techniques, where a HVS (human visual system) model is cascaded along with common imaging system performance measures (such as MTF), which relate directly to image quality attributes such as contrast, sharpness and noise. This weighted cascade process permits each performance measure to be altered independently, making the proposed metrics versatile, and simple to manipulate by engineers. Also, the proposed method does not require a reference image, which ensures the proposed metrics will be capable of assessing quality of optical capture systems, or entire imaging chains from capture to display.

During the metrics’ development, non-linearity of imaging components and processes will be investigated and modeled where possible. Non-linearities present within early stages of HVS cortical processing, will be accounted for by implementing the latest HVS sensitivity models, obtained directly from pictorial stimuli by the CVIT research team.

Once the metrics have been developed, their output will be tested against perceived image quality scores assigned to images manipulated in terms of contrast, sharpness and noise. Their correlation with this psychophysically obtained data, will then be benchmarked against other image quality metrics.

Doctoral Researchers

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