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Wavelet-Based Retinal Image Enhancement

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Book cover Image Analysis and Recognition (ICIAR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12132))

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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.

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Authors and Affiliations

  1. Department of Electronics and Communication, Faculty of Engineering, Misr International University, Cairo, Egypt

    Safinaz ElMahmoudy & Lamiaa Abdel-Hamid

  2. Department of Mathematics and Physics, Faculty of Engineering, Ain Shams University, Cairo, Egypt

    Ahmed El-Rafei

  3. Department of Electronics and Communication, Faculty of Engineering, Ain Shams University, Cairo, Egypt

    Salwa El-Ramly

Authors
  1. Safinaz ElMahmoudy
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  2. Lamiaa Abdel-Hamid
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  3. Ahmed El-Rafei
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  4. Salwa El-Ramly
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Corresponding author

Correspondence to Safinaz ElMahmoudy .

Editor information

Editors and Affiliations

  1. University of Porto, Porto, Portugal

    Aurélio Campilho

  2. University of Waterloo, Waterloo, ON, Canada

    Fakhri Karray

  3. University of Waterloo, Waterloo, ON, Canada

    Zhou Wang

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ElMahmoudy, S., Abdel-Hamid, L., El-Rafei, A., El-Ramly, S. (2020). Wavelet-Based Retinal Image Enhancement. In: Campilho, A., Karray, F., Wang, Z. (eds) Image Analysis and Recognition. ICIAR 2020. Lecture Notes in Computer Science(), vol 12132. Springer, Cham. https://doi.org/10.1007/978-3-030-50516-5_27

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  • DOI: https://doi.org/10.1007/978-3-030-50516-5_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50515-8

  • Online ISBN: 978-3-030-50516-5

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