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Gradient-based value mapping for pseudocolor images

[+] Author Affiliations
Arvind Visvanathan

University of Nebraska–Lincoln, Computer Science and Engineering Department, Lincoln, Nebraska 68588-0115

Stephen E. Reichenbach

University of Nebraska–Lincoln, Computer Science and Engineering Department, Lincoln, Nebraska 68588-0115

Qingping Tao

GC Image LLC, Lincoln, Nebraska 68505-7403

J. Electron. Imaging. 16(3), 033004 (September 20, 2007). doi:10.1117/1.2778426
History: Received November 07, 2006; Revised February 08, 2007; Accepted March 08, 2007; Published September 20, 2007
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We develop a method for automatic colorization of images (or two-dimensional fields) in order to visualize pixel values and their local differences. In many applications, local differences in pixel values are as important as their values. For example, in topography, both elevation and slope often must be considered. Gradient-based value mapping (GBVM) is a technique for colorizing pixels based on value (e.g., intensity or elevation) and gradient (e.g., local differences or slope). The method maps pixel values to a color scale (either gray-scale or pseudocolor) in a manner that emphasizes gradients in the image while maintaining ordinal relationships of values. GBVM is especially useful for high-precision data, in which the number of possible values is large. Colorization with GBVM is demonstrated with data from comprehensive two-dimensional gas chromatography (GCxGC), using both gray-scale and pseudocolor to visualize both small and large peaks, and with data from the Global Land One-Kilometer Base Elevation (GLOBE) Project, using gray-scale to visualize features that are not visible in images produced with popular value-mapping algorithms.

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© 2007 SPIE and IS&T

Citation

Arvind Visvanathan ; Stephen E. Reichenbach and Qingping Tao
"Gradient-based value mapping for pseudocolor images", J. Electron. Imaging. 16(3), 033004 (September 20, 2007). ; http://dx.doi.org/10.1117/1.2778426


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