Abstract
Getting clear high detailed images with high contrast is an important task in many spheres of science and engineering. However, it's not always possible because of imperfection of devices or environment conditions. This all leaded to development of different methods of image enhancement. In this article a developed two-phase full-color image enhancement algorithm is described. During the first phase the picture is denoised. Wavelet transformation has been chosen to perform it, because it allows easily remove high-frequency parts. Also, noise components, especially big random surges of signal, could be presented like set of local features of signals. Noise can be reduced by thresholding this features. During the second phase brightness and contrast are automatically tuned up using evolutionary algorithm. Evolutionary algorithms, which are effective methods of multidimensional optimization, allow quick selection of optimal values of transformation parameters, using objective optimization criterion.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 6522 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | Thirteenth Joint International Symposium on Atmospheric and Ocean Optics/ Atmospheric Physics - Tomsk, Russian Federation Duration: 2 Jul 2006 → 7 Jul 2006 |
Other
| Other | Thirteenth Joint International Symposium on Atmospheric and Ocean Optics/ Atmospheric Physics |
|---|---|
| Country | Russian Federation |
| City | Tomsk |
| Period | 2.7.06 → 7.7.06 |
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Keywords
- Evolutionary algorithm
- Image enhancement
- Wavelet transformation
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Condensed Matter Physics
Cite this
Applying Wavelets and Evolutionary algorithms to automatic image enhancement. / Belousov, Artem A.; Spitsyn, Vladimir G.; Sidorov, Dmitry V.
Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6522 2006. 652210.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Applying Wavelets and Evolutionary algorithms to automatic image enhancement
AU - Belousov, Artem A.
AU - Spitsyn, Vladimir G.
AU - Sidorov, Dmitry V.
PY - 2006
Y1 - 2006
N2 - Getting clear high detailed images with high contrast is an important task in many spheres of science and engineering. However, it's not always possible because of imperfection of devices or environment conditions. This all leaded to development of different methods of image enhancement. In this article a developed two-phase full-color image enhancement algorithm is described. During the first phase the picture is denoised. Wavelet transformation has been chosen to perform it, because it allows easily remove high-frequency parts. Also, noise components, especially big random surges of signal, could be presented like set of local features of signals. Noise can be reduced by thresholding this features. During the second phase brightness and contrast are automatically tuned up using evolutionary algorithm. Evolutionary algorithms, which are effective methods of multidimensional optimization, allow quick selection of optimal values of transformation parameters, using objective optimization criterion.
AB - Getting clear high detailed images with high contrast is an important task in many spheres of science and engineering. However, it's not always possible because of imperfection of devices or environment conditions. This all leaded to development of different methods of image enhancement. In this article a developed two-phase full-color image enhancement algorithm is described. During the first phase the picture is denoised. Wavelet transformation has been chosen to perform it, because it allows easily remove high-frequency parts. Also, noise components, especially big random surges of signal, could be presented like set of local features of signals. Noise can be reduced by thresholding this features. During the second phase brightness and contrast are automatically tuned up using evolutionary algorithm. Evolutionary algorithms, which are effective methods of multidimensional optimization, allow quick selection of optimal values of transformation parameters, using objective optimization criterion.
KW - Evolutionary algorithm
KW - Image enhancement
KW - Wavelet transformation
UR - http://www.scopus.com/inward/record.url?scp=33846207123&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33846207123&partnerID=8YFLogxK
U2 - 10.1117/12.723089
DO - 10.1117/12.723089
M3 - Conference contribution
SN - 0819466425
SN - 9780819466426
VL - 6522
BT - Proceedings of SPIE - The International Society for Optical Engineering
ER -