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Study of the Noise Level in the Colour Fundus Images

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Data Science (ICDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9208))

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Abstract

Diabetic Retinopathy (DR) causes vision loss insufficiency due to impediment rising from high sugar level conditions disturbing the retina. The Progression of DR occurs in the Foveal avascular zone (FAZ) due to loss of tiny blood vessels of capillary network. Due to image acquisition process of fundus camera, the colour retinal fundus image suffers from varying contrast and noise problems. To overcome varying contrast and noise problem in fundus image, the technique has been implemented. The technique is contained on the Retinex algorithm along with stationary wavelet transform. The technique has been applied on 36 high resolution fundus (HRF) image database contain the 18 bad quality images and 18 good quality images. The RETSWT (RETinex and Stationary Wavelet Transform) developed with introduces denoising techniques. Stationary wavelet transform is used as denoised technique. RETSWT achieved the average PSNR improvement of 2.39 db good quality images else it achieved the average PSNR improvement of 2.20 db in the bad quality images. The RETSWT image enhancement method potentially reduces the need of the invasive fluorescein angiogram in DR assessment.

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Acknowledgement

The research project is supported by the Australian Research Council (ARC) through the grant DP140102270.

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Authors and Affiliations

  1. School of Computing and Mathematics, Charles Sturt University, Bathurst, NSW, 2795, Australia

    Toufique Ahmed Soomro & Junbin Gao

Authors
  1. Toufique Ahmed Soomro
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  2. Junbin Gao
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Corresponding author

Correspondence to Junbin Gao .

Editor information

Editors and Affiliations

  1. University of Technology, Sydney, Australia

    Chengqi Zhang

  2. Xi'an Jiaotong University, Xi'an Jiaotong, China

    Wei Huang

  3. Chinese Academy of Sciences, Beijing, China

    Yong Shi

  4. University of Illinois Chicago, CHICAGO, Illinois, USA

    Philip S. Yu

  5. Fudan University, Shanghai, China

    Yangyong Zhu

  6. Research Center on Fictitious Econo, Chinese Academy of Sciences, Beijing, China

    Yingjie Tian

  7. University of Technology, Sydney, Australia

    Peng Zhang

  8. Victoria University, Melbourne, Victoria, Australia

    Jing He

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© 2015 Springer International Publishing Switzerland

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Soomro, T.A., Gao, J. (2015). Study of the Noise Level in the Colour Fundus Images. In: Zhang, C., et al. Data Science. ICDS 2015. Lecture Notes in Computer Science(), vol 9208. Springer, Cham. https://doi.org/10.1007/978-3-319-24474-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-24474-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24473-0

  • Online ISBN: 978-3-319-24474-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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