Paper
7 December 2001 Foveated wavelet image quality index
Zhou Wang, Alan Conrad Bovik, Ligang Lu, Jack L. Kouloheris
Author Affiliations +
Abstract
The human visual system (HVS) is highly non-uniform in sampling, coding, processing and understanding. The spatial resolution of the HVS is highest around the point of fixation (foveation point) and decreases rapidly with increasing eccentricity. Currently, most image quality measurement methods are designed for uniform resolution images. These methods do not correlate well with the perceived foveated image quality. Wavelet analysis delivers a convenient way to simultaneously examine localized spatial as well as frequency information. We developed a new image quality metric called foveated wavelet image quality index (FWQI) in the wavelet transform domain. FWQI considers multiple factors of the HVS, including the spatial variance of the contrast sensitivity function, the spatial variance of the local visual cut-off frequency, the variance of human visual sensitivity in different wavelet subbands, and the influence of the viewing distance on the display resolution and the HVS features. FWQI can be employed for foveated region of interest (ROI) image coding and quality enhancement. We show its effectiveness by using it as a guide for optimal bit assignment of an embedded foveated image coding system. The coding system demonstrates very good coding performance and scalability in terms of foveated objective as well as subjective quality measurement.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhou Wang, Alan Conrad Bovik, Ligang Lu, and Jack L. Kouloheris "Foveated wavelet image quality index", Proc. SPIE 4472, Applications of Digital Image Processing XXIV, (7 December 2001); https://doi.org/10.1117/12.449797
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Cited by 35 scholarly publications.
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KEYWORDS
Image quality

Wavelets

Image compression

Visualization

Contrast sensitivity

Discrete wavelet transforms

Image processing

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