Gradient-based value mapping for pseudocolor images

Arvind Visvanathan, Stephen E. Reichenbach, Qingping Tao

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Article number033004
JournalJournal of Electronic Imaging
Volume16
Issue number3
DOIs
StatePublished - Nov 19 2007

Fingerprint

Pixels
gray scale
gradients
pixels
slopes
Gas chromatography
Topography
gas chromatography
Color
topography
color

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Gradient-based value mapping for pseudocolor images. / Visvanathan, Arvind; Reichenbach, Stephen E.; Tao, Qingping.

In: Journal of Electronic Imaging, Vol. 16, No. 3, 033004, 19.11.2007.

Research output: Contribution to journalArticle

@article{64f64733356040c0bdde69b4eb8010c3,
title = "Gradient-based value mapping for pseudocolor images",
abstract = "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.",
author = "Arvind Visvanathan and Reichenbach, {Stephen E.} and Qingping Tao",
year = "2007",
month = "11",
day = "19",
doi = "10.1117/1.2778426",
language = "English (US)",
volume = "16",
journal = "Journal of Electronic Imaging",
issn = "1017-9909",
publisher = "SPIE",
number = "3",

}

TY - JOUR

T1 - Gradient-based value mapping for pseudocolor images

AU - Visvanathan, Arvind

AU - Reichenbach, Stephen E.

AU - Tao, Qingping

PY - 2007/11/19

Y1 - 2007/11/19

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=36048977953&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=36048977953&partnerID=8YFLogxK

U2 - 10.1117/1.2778426

DO - 10.1117/1.2778426

M3 - Article

AN - SCOPUS:36048977953

VL - 16

JO - Journal of Electronic Imaging

JF - Journal of Electronic Imaging

SN - 1017-9909

IS - 3

M1 - 033004

ER -