Three methods of detail-preserving contrast reduction for displayed images
John Erwin Tumblin, Greg Turk · UPT. Syiah Kuala University Library (Syiah Kuala University) · 1999
We are immersed in a world of high contrast scenes that we cannot directly reproduce in displayed images. Night scenes, sunny days, and glaring reflections are lled with contrasts measured in ratios of thousands or millions to one, but we use display devices such as CRTs and printers with maximum contrasts measured in tens and hundreds. How can we reduce the large contrasts of a scene suciently for display yet still preserve the small contrasts of important scene details and textures made visible by local adaptation processes in human vision? The thesis argues that we should rst separate the scene into "large features" and "fine details" and then construct the displayed image by combining compressed large features and preserved ne details. Most previous contrast-reducing methods either avoid this separation and suer some loss of fine details, or perform separations based on linear bandpass lter decompositions such as wavelets or image pyramids that introduce halo-like artifacts in displayed images. Using results and reasoning from computer vision, physiology, and visual psychophysics, this dissertation presents three new separation-based display methods for high contrast scenes and demonstrates their properties with several example images. The layering method uses a new sigmoid-shaped function, similar to the response of lm or retinal