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Wavelet and PCA-based glaucoma classification through novel methodological enhanced retinal images

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Abstract

In this paper, we have proposed a systematic retinal image enhancement and classification method. The proposed method deals with balancing all the visual and technical aspects of the image for glaucoma diagnosis. Initially, similar 3D image blocks are obtained for each retinal image using novel block-matching and grouping techniques. The proposed enhancement technique emphasizes these blocks, which constitute careful estimation of low frequency for each 3D block followed by enhancement using the new alpha-rooting method with adaptive alpha value. During this, the image may over-enhance in some areas, which can be corrected through the image polishing phase that uses cumulative distribution function (CDF) transformations. The enhanced retinal images are qualitatively compared with the outcomes of some existing methods and are employed in glaucoma classification using principal component analysis (PCA) and its variants using discrete wavelet transformations (DWT). We have carried out a deep investigation to find the best combination of DWT and PCA variants. The results obtained from the implementation proved that the performance of the proposed method is highly satisfactory.

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Acknowledgements

The fundus images used in this paper for the comparative study were collected from the Goutami Eye Institute, Rajamahendravaram-533105, Andhra Pradesh, India. We would like to express our deep and sincere gratitude to Dr. Y. Srinivas Reddy, M.S. (Ophthal), and Dr. A. Prasanth Kumar, M.S. (Ophthal), for providing corresponding information and the real fundus images.

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  1. School of Computer Science Engineering, VIT - AP University, Amaravati, 522237, India

    N. Krishna Santosh & Soubhagya Sankar Barpanda

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  1. N. Krishna Santosh
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Santosh, N.K., Barpanda, S.S. Wavelet and PCA-based glaucoma classification through novel methodological enhanced retinal images. Machine Vision and Applications 33, 11 (2022). https://doi.org/10.1007/s00138-021-01263-w

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