Abstract
While histogram modification has traditionally been used for the enhancement of color images, it has usually been restricted to processing the luminance component and, in some cases, the saturation. Reducing the problem's dimensionality in this manner generally sacrifices the ability to make full use of the color space gamut. Presented here are two novel color image contrast enhancement approaches which operate in three dimensions and aim for full gamut utilization. One is an extension of the histogram explosion algorithm to operate in CIELUV color space, intended to produce perceptually improved results compared to the original RGB method. The other is a new and very efficient recursive method, 'histogram decimation,' whose output is roughly similar to that of the RGB histogram explosion algorithm. Both algorithms are briefly discussed along with their major characteristics. A direct comparison follows, based on processing a set of standard test images. The performance analysis quantitatively compares the computation time and the mean-squared error in the cdf vs. an ideal, uniform distribution.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE International Conference on Image Processing |
| Editors | Anon |
| Publisher | IEEE |
| Pages | 1015-1018 |
| Number of pages | 4 |
| Volume | 3 |
| State | Published - 1996 |
| Externally published | Yes |
| Event | Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz Duration: Sep 16 1996 → Sep 19 1996 |
Other
| Other | Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) |
|---|---|
| City | Lausanne, Switz |
| Period | 9/16/96 → 9/19/96 |
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ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Hardware and Architecture
- Electrical and Electronic Engineering
Cite this
3-D histogram modification of color images. / Mlsna, Phillip A; Zhang, Qiang; Rodriguez, Jeffrey J.
IEEE International Conference on Image Processing. ed. / Anon. Vol. 3 IEEE, 1996. p. 1015-1018.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - 3-D histogram modification of color images
AU - Mlsna, Phillip A
AU - Zhang, Qiang
AU - Rodriguez, Jeffrey J.
PY - 1996
Y1 - 1996
N2 - While histogram modification has traditionally been used for the enhancement of color images, it has usually been restricted to processing the luminance component and, in some cases, the saturation. Reducing the problem's dimensionality in this manner generally sacrifices the ability to make full use of the color space gamut. Presented here are two novel color image contrast enhancement approaches which operate in three dimensions and aim for full gamut utilization. One is an extension of the histogram explosion algorithm to operate in CIELUV color space, intended to produce perceptually improved results compared to the original RGB method. The other is a new and very efficient recursive method, 'histogram decimation,' whose output is roughly similar to that of the RGB histogram explosion algorithm. Both algorithms are briefly discussed along with their major characteristics. A direct comparison follows, based on processing a set of standard test images. The performance analysis quantitatively compares the computation time and the mean-squared error in the cdf vs. an ideal, uniform distribution.
AB - While histogram modification has traditionally been used for the enhancement of color images, it has usually been restricted to processing the luminance component and, in some cases, the saturation. Reducing the problem's dimensionality in this manner generally sacrifices the ability to make full use of the color space gamut. Presented here are two novel color image contrast enhancement approaches which operate in three dimensions and aim for full gamut utilization. One is an extension of the histogram explosion algorithm to operate in CIELUV color space, intended to produce perceptually improved results compared to the original RGB method. The other is a new and very efficient recursive method, 'histogram decimation,' whose output is roughly similar to that of the RGB histogram explosion algorithm. Both algorithms are briefly discussed along with their major characteristics. A direct comparison follows, based on processing a set of standard test images. The performance analysis quantitatively compares the computation time and the mean-squared error in the cdf vs. an ideal, uniform distribution.
UR - http://www.scopus.com/inward/record.url?scp=0030384484&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0030384484&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0030384484
VL - 3
SP - 1015
EP - 1018
BT - IEEE International Conference on Image Processing
A2 - Anon, null
PB - IEEE
ER -