Skip to main content

2015 | OriginalPaper | Buchkapitel

A New Method of Object Saliency Detection in Foggy Images

verfasst von : Wenjun Lu, Xiaoning Sun, Congli Li

Erschienen in: Image and Graphics

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Aiming to saliency detection problem of degraded foggy images, a new method of object saliency detection method in foggy images based on region covariance matrix is presented. In the method, color, direction and space information are extracted to form covariance feature description matrix according to characteristics of foggy images. Then local saliency sub-map is acquired by local contrast. In the same time, Wiener filter and Sobel edge detection are used to obtain global saliency sub-map. Finally, local saliency map of color domain is optimized by edge global saliency map, and saliency map is completed. Experiments show that compared with state-of-art methods, the proposed method has better adaptability and accuracy to object saliency detection in foggy images.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Koch, C., Ullman, S.: Shifts in selective visual attention: towards the underlying neural circuitry. Hum. Neurbiology 4, 219–227 (1985) Koch, C., Ullman, S.: Shifts in selective visual attention: towards the underlying neural circuitry. Hum. Neurbiology 4, 219–227 (1985)
2.
Zurück zum Zitat Borji, A., Cheng, M.M., Jiang, H.Z., Li, J.: Salient object detection: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) (2014, accepted) Borji, A., Cheng, M.M., Jiang, H.Z., Li, J.: Salient object detection: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) (2014, accepted)
3.
Zurück zum Zitat He, K.M., Sun, J., Zhou, X.O.: Single image haze removal using dark channel prior. In: Proceedings of IEEE Conference on Computer Vision Pattern Recognition (CVPR), pp. 1956–1963. IEEE, Washington DC (2009) He, K.M., Sun, J., Zhou, X.O.: Single image haze removal using dark channel prior. In: Proceedings of IEEE Conference on Computer Vision Pattern Recognition (CVPR), pp. 1956–1963. IEEE, Washington DC (2009)
4.
Zurück zum Zitat Jing, Y.U., DaPeng, L., QingMin, L.: Physics-based fast single image fog removal. ACTA AUTOMATICA SINICA 37(2), 143–149 (2011)CrossRef Jing, Y.U., DaPeng, L., QingMin, L.: Physics-based fast single image fog removal. ACTA AUTOMATICA SINICA 37(2), 143–149 (2011)CrossRef
5.
Zurück zum Zitat Fan, G., Zixing, C., Bin, X., et al.: New algorithm of automatic haze removal for single image. J. Image Grap. 16(4), 516–521 (2011) Fan, G., Zixing, C., Bin, X., et al.: New algorithm of automatic haze removal for single image. J. Image Grap. 16(4), 516–521 (2011)
6.
Zurück zum Zitat Li, C., Lu, W., Xue, S., Shi, Y.: Research on quality improvement of polarization imaging in foggy conditions. In: Sun, C., Fang, F., Zhou, Z.-H., Yang, W., Liu, Z.-Y. (eds.) IScIDE 2013. LNCS, vol. 8261, pp. 208–215. Springer, Heidelberg (2013)CrossRef Li, C., Lu, W., Xue, S., Shi, Y.: Research on quality improvement of polarization imaging in foggy conditions. In: Sun, C., Fang, F., Zhou, Z.-H., Yang, W., Liu, Z.-Y. (eds.) IScIDE 2013. LNCS, vol. 8261, pp. 208–215. Springer, Heidelberg (2013)CrossRef
7.
Zurück zum Zitat Li, C., Lu, W., Xue, S., Shi, Y., Sun, X.: Quality assessment of polarization analysis images in foggy conditions. In: Proceedings of the IEEE International Conference on Image Processing(ICIP), pp. 551–555. IEEE, Pairs (2014) Li, C., Lu, W., Xue, S., Shi, Y., Sun, X.: Quality assessment of polarization analysis images in foggy conditions. In: Proceedings of the IEEE International Conference on Image Processing(ICIP), pp. 551–555. IEEE, Pairs (2014)
8.
Zurück zum Zitat Tuzel, O., Porikli, F., Meer, P.: Region covariance: a fast descriptor for detection and classification. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 589–600. Springer, Heidelberg (2006)CrossRef Tuzel, O., Porikli, F., Meer, P.: Region covariance: a fast descriptor for detection and classification. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 589–600. Springer, Heidelberg (2006)CrossRef
9.
Zurück zum Zitat Föerstner, W., Moonen, B.: A metric for covariance matrices. Technical report, Department of Geodesy and Geoinformatics, Stuttgart University (1999) Föerstner, W., Moonen, B.: A metric for covariance matrices. Technical report, Department of Geodesy and Geoinformatics, Stuttgart University (1999)
10.
Zurück zum Zitat Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 2012, 54–125 (1998) Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 2012, 54–125 (1998)
11.
Zurück zum Zitat Harel, J., Koch, C., Perona, P.: Graph-based visual saliency. In: Advances in Neural Information Process Systems(NIPS), pp. 545–552. MIT Press, Massachusetts (2007) Harel, J., Koch, C., Perona, P.: Graph-based visual saliency. In: Advances in Neural Information Process Systems(NIPS), pp. 545–552. MIT Press, Massachusetts (2007)
12.
Zurück zum Zitat Achanta, R., Hemami, S., Estrada, F., Süsstrunk, S.: Frequency-tuned salient region detection. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), p. 1597. IEEE, Miami (2009) Achanta, R., Hemami, S., Estrada, F., Süsstrunk, S.: Frequency-tuned salient region detection. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), p. 1597. IEEE, Miami (2009)
13.
Zurück zum Zitat Zhang, L., Gu, Z.Y., Zhang, H.Y.: SDSP : a novel saliency detection method by combing simple priors. In: Proceedings of the IEEE International Conference on Image Processing(ICIP), pp. 171–175. Springer, Melbourne (2013) Zhang, L., Gu, Z.Y., Zhang, H.Y.: SDSP : a novel saliency detection method by combing simple priors. In: Proceedings of the IEEE International Conference on Image Processing(ICIP), pp. 171–175. Springer, Melbourne (2013)
14.
Zurück zum Zitat Margolin, R., Tal, A., Zelnik-Manor, L.: What makes a patch distinct. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), pp. 1139–1146. IEEE, Portland (2013) Margolin, R., Tal, A., Zelnik-Manor, L.: What makes a patch distinct. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), pp. 1139–1146. IEEE, Portland (2013)
Metadaten
Titel
A New Method of Object Saliency Detection in Foggy Images
verfasst von
Wenjun Lu
Xiaoning Sun
Congli Li
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-21978-3_19

Premium Partner