Abstract
An approach to image enhancement through artificial neural network's (ANN) processing is proposed. The structure and weights of ANN are tuned with use of evolutionary concept. Each image is processed in pixel-by-pixel manner using pixels' local characteristics that are calculated approximately to increase the processing speed but preserving satisfactory calculations' error. The three-step procedure for image enhancement is proposed: (1) image brightness preprocessing; (2) local level processing using ANN; (3) global level autoleveling algorithm. The results for the proposed three-step image enhancement procedure are presented.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2009 |
| Pages | 833-838 |
| Number of pages | 6 |
| Volume | 2 |
| Publication status | Published - 2009 |
| Event | 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2009 - Las Vegas, NV, United States Duration: 13 Jul 2009 → 16 Jul 2009 |
Other
| Other | 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2009 |
|---|---|
| Country | United States |
| City | Las Vegas, NV |
| Period | 13.7.09 → 16.7.09 |
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Keywords
- Image enhancement
- Neuroevolution
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
Cite this
Neuroevolutionary digital image processing. / Spitsyn, V.; Tsoy, Y.
Proceedings of the 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2009. Vol. 2 2009. p. 833-838.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Neuroevolutionary digital image processing
AU - Spitsyn, V.
AU - Tsoy, Y.
PY - 2009
Y1 - 2009
N2 - An approach to image enhancement through artificial neural network's (ANN) processing is proposed. The structure and weights of ANN are tuned with use of evolutionary concept. Each image is processed in pixel-by-pixel manner using pixels' local characteristics that are calculated approximately to increase the processing speed but preserving satisfactory calculations' error. The three-step procedure for image enhancement is proposed: (1) image brightness preprocessing; (2) local level processing using ANN; (3) global level autoleveling algorithm. The results for the proposed three-step image enhancement procedure are presented.
AB - An approach to image enhancement through artificial neural network's (ANN) processing is proposed. The structure and weights of ANN are tuned with use of evolutionary concept. Each image is processed in pixel-by-pixel manner using pixels' local characteristics that are calculated approximately to increase the processing speed but preserving satisfactory calculations' error. The three-step procedure for image enhancement is proposed: (1) image brightness preprocessing; (2) local level processing using ANN; (3) global level autoleveling algorithm. The results for the proposed three-step image enhancement procedure are presented.
KW - Image enhancement
KW - Neuroevolution
UR - http://www.scopus.com/inward/record.url?scp=84864960959&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864960959&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84864960959
SN - 9781601321190
VL - 2
SP - 833
EP - 838
BT - Proceedings of the 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2009
ER -