Visual perception studies to improve the perceived sharpness of television images

William E. Glenn

doi:10.1117/12.469542

30 May 2002 Visual perception studies to improve the perceived sharpness of television images

William E. Glenn

Proceedings Volume 4662, Human Vision and Electronic Imaging VII; (2002) https://doi.org/10.1117/12.469542
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

In this paper several properties of visual perception are used to describe the perceived sharpness of present HDTV transmission and display formats. A method is described that uses these properties to improve perceived sharpness without increasing the transmission bit rate. Because of the oblique effect in vision and the statistical orientation of lines in scenes, diagonal sampling reduces the required number of pixels in an image. Quantitatively, our measurements show that the number of pixels is reduced by a factor of 1.4 for the same perceived sharpness. Interlaced scanning reduces vertical resolution for several reasons involving spatial and temporal masking effects in visual perception. Progressive scan avoids these limitations. In addition, by taking advantage of the octave-wide tuning bands in visual perception, our measurements show that the perceived resolution in the vertical direction for a progressive scan can be double that of an interlaced scan. By using diagonal sampling, a 1920X1080 image with progressive scan at 60 frames per second requires the same transmission bit rate as a 1920X1080 cardinally sampled image scanned interlaced at 30 frames per second. This results in an image that appears to be much sharper than the 1080 line interlaced format without the interlace artifacts.

Citation Download Citation

William E. Glenn "Visual perception studies to improve the perceived sharpness of television images", Proc. SPIE 4662, Human Vision and Electronic Imaging VII, (30 May 2002); https://doi.org/10.1117/12.469542

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KEYWORDS

Visualization

Image resolution

Spatial frequencies

Televisions

Cameras

Contrast sensitivity

Image filtering

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