IMAGE ENHANCEMENT BY REGION DETECTION ON CFA DATA IMAGES

S. Battiato, S. Cariolo, G. Gallo, G. Di Blasi

Abstract

The paper proposes a new method devoted to identify specific semantic regions on CFA (Color Filtering Array) data images representing natural scenes. Making use of collected statistics over a large dataset of high quality natural images, the method uses spatial features and the Principal Component Analysis (PCA) in the HSL and normalized-RG color spaces. The classes considered, taking into account “visual significance”, are skin, vegetation, blue sky and sea. Semantic information are obtained on pixel basis leading to meaningful regions although not spatially coherent. Such information is used for automatic color rendition of natural digital images based on adaptive color correction. The overall method outperforms previous results providing reliable information validated by measured and subjective experiments.

References

  1. Abdou, I.E., Pratt, W.K., 1979. Qualitative Design and Evaluation of Enhancement/Thresholding Edge Detector, Proceedings of IEEE, vol. 67, No. 5, pp. 753-763.
  2. Battiato, S., Mancuso, M., Bosco, A., Guarnera, M., 2001. Psychovisual and Statistical Optimization of Quantization Tables for DCT Compression Engines. International Conference on Image Analysis and Processing 2001, pp. 602-606.
  3. Battiato, S., Bosco, A., Castorina, A., Messina, G., 2004. Automatic Image Enhancement by Content Dependent Exposure Correction. EURASIP Journal on Applied Signal Processing, Vol. 12, pp. 1849-1860.
  4. Bayer, B.E, 1976. Color Imaging Array. U.S. Patent 3971065.
  5. Bosco, A., Mancuso, M., Battiato, S., Spampinato, G., 2002. Temporal Noise Reduction of Bayer Matrixed Video Data. International Conference on Multimedia and Expo 2002, pp.681-684.
  6. Comaniciu, D., Meer, D., 1997. Robust Analysis of Feature Spaces: Color Image Segmentation. Conf. Computer Vision and Pattern Recognition, pp. 750- 755.
  7. Fredembach, C., Schröder, M., Süsstrunk, S., 2004. Eigenregions for Image Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 26 (12), pp. 1645-1649.
  8. Lukac, R., Martin, K., Platanoitis, K.N., 2004. Digital Camera Zooming Based on Unified CFA image Processing Steps. IEEE Trans. on Cons. Electronics, Vol.50, (1), pp. 15-24.
  9. Luo, J., Etz, S.P., 2003. A Physical Model-based Approach to Detecting Sky in Photographic Images. IEEE Transactions on Image Processing, Vol. 3 (11).
  10. Lee, E.J., Ha, Y.H., 1998. Favorite Color Correction for Favorite Colors. IEEE Trans. On Consumer Electronics, Vol. 44 (1), pp. 10-15.
  11. MPEG Requirements Group, 2001. Description of MPEG7 Content Set, ISO/IEC/JTC1/SC29/WG11/N2467.
  12. Naccari, F., Battiato, S., Bruna, A., Cariolo, S., Castorina, A., 2004. Natural Scenes Enhancement by Adaptive Color Correction. IEEE ISCE International Symposium on Consumer Electronic, pp. 320-323.
  13. Naccari, F., Battiato, S., Bruna, A., Capra, A., Castorina, A., 2005. Natural Scene Classification for Color Enhancement. IEEE Trans. on Cons. Electronics, Vol. 5 (1), pp.234-239.
  14. Yendrikhovskij, S.N., Blommaert, F.J.J , De Ridder, H., 1998. Optimizing color reproduction of natural images. Sixth Color Imaging Conference: Color Science, Systems, and Applications, pp. 140 145.
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Paper Citation


in Harvard Style

Battiato S., Cariolo S., Gallo G. and Di Blasi G. (2007). IMAGE ENHANCEMENT BY REGION DETECTION ON CFA DATA IMAGES . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 200-207. DOI: 10.5220/0002067402000207


in Bibtex Style

@conference{visapp07,
author={S. Battiato and S. Cariolo and G. Gallo and G. Di Blasi},
title={IMAGE ENHANCEMENT BY REGION DETECTION ON CFA DATA IMAGES},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2007},
pages={200-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002067402000207},
isbn={978-972-8865-74-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - IMAGE ENHANCEMENT BY REGION DETECTION ON CFA DATA IMAGES
SN - 978-972-8865-74-0
AU - Battiato S.
AU - Cariolo S.
AU - Gallo G.
AU - Di Blasi G.
PY - 2007
SP - 200
EP - 207
DO - 10.5220/0002067402000207