Faculty Publications

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  • Item
    Non-local Gradient Fidelity Model for Multiplicative Gamma Noise Removal
    (Institute of Electrical and Electronics Engineers Inc., 2018) Banothu, B.; Jidesh, P.
    In this paper a non-local gradient vector flow model is designed for restoration of images corrupted with Gamma distributed (speckle) noise and linear blurring artefacts. The filter effectively preserves edges and finer details in the course of its evolution due to the presence of the non-local TV based diffusion term and the piecewise linear approximation is reduced considerably by the gradient fidelity term present in the model. The model is found suitable for restoration of various images from the field of satellite and clinical imaging. The experimental results are shown and compared for different image data sets both visually and qualitatively using various statistical measures. © 2017 IEEE.
  • Item
    Image despeckling with non-local total bounded variation regularization
    (Elsevier Ltd, 2018) Padikkal, P.; Banothu, B.
    A non-local total bounded variational (TBV) regularization model is proposed for restoring images corrupted with data-correlated speckles and linear blurring artifacts. The energy functional of the model is derived using maximum a posteriori (MAP) estimate of the noise probability density function (PDF). The non-local total bounded variation prior regularizes the model while the data fidelity is derived using the MAP estimator of the noise PDF. The computational efficiency of the model is improved using a fast numerical scheme based on the Augmented Lagrange formulation. The proposed model is employed to restore ultrasound (US) and synthetic aperture radar (SAR) images, which are usually speckled and blurred. The numerical results are presented and compared. Furthermore, a detailed theoretical study of the model is performed in addition to the experimental analysis. © 2017 Elsevier Ltd