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Statistical modeling and Gaussianization procedure based de-speckling algorithm for retinal OCT images

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Abstract

This paper presents a de-noising method for speckle noise removal called de-speckling, retinal optical coherence tomography image by combining the features of wavelet transform, statistical modeling, Bayesian estimators and Gaussianization procedure. De-speckling methods based on statistical modeling of wavelet coefficients depend on the correct estimation of probability density function (PDF). The density estimation problem has been solved by using the Gaussianization procedure. The dynamic range capability of Gaussian PDF has been used for sharp estimation of density. A Cauchy PDF is used for modeling wavelet coefficients and finding the cumulative distribution function (CDF) of wavelet coefficients. This CDF is used as the input to the Gaussianization procedure, where it equalizes with the Gaussian CDF to estimate the density function of wavelet coefficients. Finally, the wavelet coefficients are recovered using Bayesian minimum mean square error estimator. Both visual and quantitative comparisons are performed for demonstrating the prominence of the proposed method. From simulation result it is seen that the proposed method outperforms the state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity, correlation coefficient (CoC) and edge preservation index (EPI). The proposed method has been achieved improvement of 5.13% in PSNR, 2.44% in SSIM, 2.11% in CoC and 3.45% in EPI over the well accepted existing method.

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Acknowledgements

The authors would like to thank Dr. MK Singh, Department of Ophthalmology, Institute of Medical Sciences, Banaras Hindu University (BHU), Varanasi, India, for providing the valuable data and insight. We are sincerely thankful to the potential/ anonymous reviewer’s for their critical comments and suggestions to improve the quality of the paper.

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Authors and Affiliations

  1. Dr. A. P. J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India

    Sima Sahu

  2. Department of Electronics Engineering, Kamla Nehru Institute of Technology (KNIT), Sultanpur, Uttarpradesh, India

    Harsh Vikram Singh

  3. Department of Electronics and Communication Engineering, Motilal Nehru NIT, Allahabad, India

    Basant Kumar

  4. Department of Computer Science and Engineering, Jaypee University of Information Technology Waknaghat, Solan, Himachal Pradesh, India

    Amit Kumar Singh

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  1. Sima Sahu
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  2. Harsh Vikram Singh
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Correspondence to Amit Kumar Singh.

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Sahu, S., Singh, H.V., Kumar, B. et al. Statistical modeling and Gaussianization procedure based de-speckling algorithm for retinal OCT images. J Ambient Intell Human Comput 15, 1125–1138 (2024). https://doi.org/10.1007/s12652-018-0823-2

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