Skip to main content

2020 | OriginalPaper | Buchkapitel

Wavelet-Based Retinal Image Enhancement

verfasst von : Safinaz ElMahmoudy, Lamiaa Abdel-Hamid, Ahmed El-Rafei, Salwa El-Ramly

Erschienen in: Image Analysis and Recognition

Verlag: Springer International Publishing

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

search-config
loading …

Abstract

Retinal images provide a simple non-invasive method for the detection of several eye diseases. However, many factors can result in the degradation of the images’ quality, thus affecting the reliability of the performed diagnosis. Enhancement of retinal images is thus essential to increase the overall image quality. In this work, a wavelet-based retinal image enhancement algorithm is proposed that considers four different common quality issues within retinal images (1) noise removal, (2) sharpening, (3) contrast enhancement and (4) illumination enhancement. Noise removal and sharpening are performed by processing the wavelet detail subbands, such that the upper detail coefficients are eliminated, whereas bilinear mapping is used to enhance the lower detail coefficients based on their relevance. Contrast and illumination enhancement involve applying contrast limited adaptive histogram equalization (CLAHE) and the proposed luminance boosting method to the approximation subband, respectively. Four different retinal image quality measures are computed to assess the proposed algorithm and to compare its performance against four other methods from literature. The comparison showed that the introduced method resulted in the highest overall image improvement followed by spatial CLAHE for all the considered quality measures; thus, indicating the superiority of the proposed wavelet-based enhancement method.

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 WHO: World Report on vision: executive summary (2019) WHO: World Report on vision: executive summary (2019)
3.
Zurück zum Zitat Youssif, A.A., Ghalwash, A.Z., Ghoneim, A.S.: Comparative study of contrast enhancement and illumination equalization methods for retinal vasculature segmentation. In: Cairo International Biomedical Engineering Conference, pp. 1–5 (2006) Youssif, A.A., Ghalwash, A.Z., Ghoneim, A.S.: Comparative study of contrast enhancement and illumination equalization methods for retinal vasculature segmentation. In: Cairo International Biomedical Engineering Conference, pp. 1–5 (2006)
5.
Zurück zum Zitat Yu, H., Agurto, C., Barriga, S., Nemeth, S.C., Soliz, P., Zamora, G.: Automated image quality evaluation of retinal fundus photographs in diabetic retinopathy screening. In: IEEE Southwest Symposium on Image Analysis Interpretation, pp. 125–128 (2012) Yu, H., Agurto, C., Barriga, S., Nemeth, S.C., Soliz, P., Zamora, G.: Automated image quality evaluation of retinal fundus photographs in diabetic retinopathy screening. In: IEEE Southwest Symposium on Image Analysis Interpretation, pp. 125–128 (2012)
8.
Zurück zum Zitat Jintasuttisak, T., Intajag, S.: Color retinal image enhancement by Rayleigh contrast-limited adaptive histogram equalization. In: IEEE 14th International Conference on Control Automation and Systems (ICCAS), pp. 692–697 (2014) Jintasuttisak, T., Intajag, S.: Color retinal image enhancement by Rayleigh contrast-limited adaptive histogram equalization. In: IEEE 14th International Conference on Control Automation and Systems (ICCAS), pp. 692–697 (2014)
12.
Zurück zum Zitat Ninassi, A., Le Meur, O., Le Callet, P., Barba, D.: On the performance of human visual system based image quality assessment metric using wavelet domain. In: SPIE Human Vision Electronic Imaging XIII, vol. 6806, pp. 680610–680611 (2008). https://doi.org/10.1117/12.766536 Ninassi, A., Le Meur, O., Le Callet, P., Barba, D.: On the performance of human visual system based image quality assessment metric using wavelet domain. In: SPIE Human Vision Electronic Imaging XIII, vol. 6806, pp. 680610–680611 (2008). https://​doi.​org/​10.​1117/​12.​766536
15.
Zurück zum Zitat Soomro, T.A., Gao, J., Khan, M.A.U., Khan, T.M., Paul, M.: Role of image contrast enhancement technique for ophthalmologist as diagnostic tool for diabetic retinopathy. In: International Conference on Digital Image Computing: Technical Applications DICTA, pp. 1–8 (2016). https://doi.org/10.1109/DICTA.2016.7797078 Soomro, T.A., Gao, J., Khan, M.A.U., Khan, T.M., Paul, M.: Role of image contrast enhancement technique for ophthalmologist as diagnostic tool for diabetic retinopathy. In: International Conference on Digital Image Computing: Technical Applications DICTA, pp. 1–8 (2016). https://​doi.​org/​10.​1109/​DICTA.​2016.​7797078
19.
Zurück zum Zitat Walter, T., Klein, J.C.: Automatic analysis of color fundus photographs and its application to the diagnosis of diabetic retinopathy. In: Suri, J.S., Wilson, D.L., Laxminarayan, S. (eds.) Handbook of Biomedical Image Analysis. ITBE, pp. 315–368. Springer, Boston (2007). https://doi.org/10.1007/0-306-48606-7_7CrossRef Walter, T., Klein, J.C.: Automatic analysis of color fundus photographs and its application to the diagnosis of diabetic retinopathy. In: Suri, J.S., Wilson, D.L., Laxminarayan, S. (eds.) Handbook of Biomedical Image Analysis. ITBE, pp. 315–368. Springer, Boston (2007). https://​doi.​org/​10.​1007/​0-306-48606-7_​7CrossRef
20.
Zurück zum Zitat Stefanou, H., Kakouros, S., Cavouras, D., Wallace, M.: Wavelet-based mammographic enhancement. In: 5th International Networking Conference INC, pp. 553–560 (2005) Stefanou, H., Kakouros, S., Cavouras, D., Wallace, M.: Wavelet-based mammographic enhancement. In: 5th International Networking Conference INC, pp. 553–560 (2005)
23.
Zurück zum Zitat Abdel Hamid, L.S., El-Rafei, A., El-Ramly, S., Michelson, G., Hornegger, J.: No-reference wavelet based retinal image quality assessment. In: 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing VipIMAGE, pp. 123–130 (2016) Abdel Hamid, L.S., El-Rafei, A., El-Ramly, S., Michelson, G., Hornegger, J.: No-reference wavelet based retinal image quality assessment. In: 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing VipIMAGE, pp. 123–130 (2016)
25.
Zurück zum Zitat Köhler, T., Budai, A., Kraus, M.F., Odstrčilik, J., Michelson, G., Hornegger, J.: Automatic no-reference quality assessment for retinal fundus images using vessel segmentation. In: Proceedings of the IEEE 26th Symposium Computer-Based Medical Systems CBMS, pp. 95–100 (2013). https://doi.org/10.1109/CBMS.2013.6627771 Köhler, T., Budai, A., Kraus, M.F., Odstrčilik, J., Michelson, G., Hornegger, J.: Automatic no-reference quality assessment for retinal fundus images using vessel segmentation. In: Proceedings of the IEEE 26th Symposium Computer-Based Medical Systems CBMS, pp. 95–100 (2013). https://​doi.​org/​10.​1109/​CBMS.​2013.​6627771
Metadaten
Titel
Wavelet-Based Retinal Image Enhancement
verfasst von
Safinaz ElMahmoudy
Lamiaa Abdel-Hamid
Ahmed El-Rafei
Salwa El-Ramly
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-50516-5_27