J
John D. Austin
Researcher at University of North Carolina at Chapel Hill
Publications - 11
Citations - 3519
John D. Austin is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Adaptive histogram equalization & Pixel. The author has an hindex of 9, co-authored 11 publications receiving 2854 citations.
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Journal ArticleDOI
Adaptive histogram equalization and its variations
Stephen M. Pizer,Stephen M. Pizer,E. Philip Amburn,E. Philip Amburn,John D. Austin,Robert Cromartie,Ari Geselowitz,Ari Geselowitz,Trey Greer,Bart M. ter Haar Romeny,John B. Zimmerman,John B. Zimmerman +11 more
TL;DR: It is concluded that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clip ahe can be made adequately fast to be routinely applied in the normal display sequence.
Journal ArticleDOI
Fast spheres, shadows, textures, transparencies, and imgage enhancements in pixel-planes
Henry Fuchs,Jack Goldfeather,Jeff P. Hultquist,Susan Spach,John D. Austin,Frederick P. Brooks,John Eyles,John S. Poulton +7 more
TL;DR: This paper reports on a variety of algorithms that exploit a tree of one-bit adders that can evaluate linear expressions Ax+By+C for every pixel simultaneously, as fast as the ALUs and the memory circuits can accept the results.
Proceedings Article
Fast Spheres, Shadows, Textures, Transparencies, and Image Enhancements in Pixel-Planes
Henry Fuchs,Jack Goldfeather,Jeff P. Hultquist,Susan Spach,John D. Austin,Frederick P. Brooks,John Eyles,John W. Poulton +7 more
TL;DR: Pixel-planes as discussed by the authors is a logic-enhanced memory system for raster graphics and imaging that uses a tree of one-bit adders that can evaluate linear expressions Ax+By+C for every pixel (x,y) simultaneously, as fast as the ALUs and the memory circuits can accept the results.
Proceedings ArticleDOI
Adaptive Histogram Equalization For Automatic Contrast Enhancement Of Medical Images
TL;DR: A new contrast limited form of ahe appears to allow its application to a wide variety of medical images, and a VLSI machine design is presented that will allow the calculation of a he in a fraction of a second per megapixel.