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Retinal Image Enhancement via a Multiscale Morphological Approach with OCCO Filter

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Information Technology and Systems (ICITS 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1330))

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Abstract

Retinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very important to enhance the visual quality of such images. Contrast enhancement is a pre-processing applied to images to improve their visual quality. This technique betters the identification of retinal structures in degraded retinal images. In this work, a novel algorithm based on multi-scale mathematical morphology is presented. First, the original image is blurred using the Open-Close Close-Open (OCCO) filter to reduce any artifacts in the image. Next, multiple bright and dark features are extracted from the filtered image by the Top-Hat transform. Finally, the maximum bright values are added to the original image and the maximum dark values are subtracted from the original image, previously adjusted by a weight. The algorithm was tested on 397 retinal images from the public STARE database. The proposed algorithm was compared with state of the art algorithms and results show that the proposal is more efficient in improving contrast, maintaining similarity with the original image and introducing less distortion than the other algorithms. According to ophthalmologists, the algorithm, by improving retinal images, provides greater clarity in the blood vessels of the retina and would facilitate the identification of pathologies.

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Acknowledgment

This research was funded by CONACYT, Paraguay, grant number PINV18-846.

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Authors and Affiliations

  1. Universidad Americana, Asunción, Paraguay

    Julio César Mello Román, José Luis Vázquez Noguera & Miguel García-Torres

  2. Facultad de Ciencias Exactas y Tecnológicas, Universidad Nacional de Concepción, Concepción, Paraguay

    Julio César Mello Román

  3. Division of Computer Science, Universidad Pablo de Olavide, 41013, Seville, Spain

    Miguel García-Torres

  4. Departamento de Retina, Catedra de Oftalmología, Hospital de Clínicas, Facultad de Ciencias Médicas, Universidad Nacional de Asunción, San Lorenzo, Paraguay

    Veronica Elisa Castillo Benítez & Ingrid Castro Matto

Authors
  1. Julio César Mello Román
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  2. José Luis Vázquez Noguera
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  3. Miguel García-Torres
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  4. Veronica Elisa Castillo Benítez
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  5. Ingrid Castro Matto
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Corresponding author

Correspondence to José Luis Vázquez Noguera .

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Editors and Affiliations

  1. ISEG, University of Lisboa, Lisboa, Portugal

    Álvaro Rocha

  2. Geografía, University of Santiago de Compostela, Santiago de Compostela, Spain

    Carlos Ferrás

  3. Ciencia Política y Sociología, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Paulo Carlos López-López

  4. Campus UPSE, Universidad Estatal Peninsula de Santa Elena Sistemas, La Libertad, Ecuador

    Teresa Guarda

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Román, J.C.M., Noguera, J.L.V., García-Torres, M., Benítez, V.E.C., Matto, I.C. (2021). Retinal Image Enhancement via a Multiscale Morphological Approach with OCCO Filter. In: Rocha, Á., Ferrás, C., López-López, P.C., Guarda, T. (eds) Information Technology and Systems. ICITS 2021. Advances in Intelligent Systems and Computing, vol 1330. Springer, Cham. https://doi.org/10.1007/978-3-030-68285-9_18

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