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2D Wavelet Tree Ordering Based Localized Total Variation Model for Efficient Image Restoration

Jawaharlal Nehru Technological University, Kakinada, GITAM, Deemed to be University, Kakinada, Andhra Pradesh and Hyderabad, Telangana, India

E-mail Address: praveen416.kumar@gmail.com

Corresponding author.

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C. Venkata Narasimhulu

Department of Electronics and Communication Engineering, Lords Institute of Engineering & Technology, Hyderabad, Telangana, India

E-mail Address: narasimhulucv@gmail.com

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K. Satya Prasad

Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University Kakinada, Kakinada, Andhra Pradesh, India

E-mail Address: prasad_kodati@yahoo.co.in

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https://doi.org/10.1142/S0219467822400095Cited by:0 (Source: Crossref)

This article is part of the issue:

Special Issue on Advances in Deep Learning Algorithms for Brain Imaging
Guest Editor: Dr. Bala Anand Muthu

Abstract

The degraded image during the process of image analysis needs more number of iterations to restore it. These iterations take long waiting time and slow scanning, resulting in inefficient image restoration. A few numbers of measurements are enough to recuperate an image with good condition. Due to tree sparsity, a 2D wavelet tree reduces the number of coefficients and iterations to restore the degraded image. All the wavelet coefficients are extracted with overlaps as low and high sub-band space and ordered them such that they are decomposed in the tree ordering structured path. Some articles have addressed the problems with tree sparsity and total variation (TV), but few authors endorsed the benefits of tree sparsity. In this paper, a spatial variation regularization algorithm based on tree order is implemented to change the window size and variation estimators to reduce the loss of image information and to solve the problem of image smoothing operation. The acceptance rate of the tree-structured path relies on local variation estimators to regularize the performance parameters and update them to restore the image. For this, the Localized Total Variation (LTV) method is proposed and implemented on a 2D wavelet tree ordering structured path based on the proposed image smooth adjustment scheme. In the end, a reliable reordering algorithm proposed to reorder the set of pixels and to increase the reliability of the restored image. Simulation results clearly show that the proposed method improved the performance compared to existing methods of image restoration.

Keywords:

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