Projected Improved Fista and Application to Image Deblurring

Pokala, PK and Seelamantula, CS (2020) Projected Improved Fista and Application to Image Deblurring. In: IEEE International Conference on Image Processing, ICIP 2020, 25-28, September 2020, Abu Dhabi United Arab Emirates, pp. 1043-1047.

PDF Pro-Int-2020.pdf - Published Version Restricted to Registered users only Download (282kB) | Request a copy

Abstract

The analysis-sparse model has been shown to be efficient as compared to the synthesis-sparse model when the sparsifying transform is redundant particularly for image restoration applications. We pose the image deblurring problem as an optimization problem based on the analysis-sparse model considering the sparsifying basis to be a tight frame, more specifically, the shift-invariant discrete wavelet transform (SIDWT). We propose two algorithms, namely, projected improved fast iterative soft-thresholding algorithm (piFISTA) and projected improved fast iterative soft-thresholding algorithm beyond Nesterov's momentum (piFISTA-BN). The proposed algorithms are the analysis counterparts of the improved fast iterative soft-thresholding algorithm (iFISTA) and improved fast iterative soft-thresholding algorithm beyond Nesterov's momentum (iFISTA-BN), respectively, both of which consider the synthesis-sparse model. We demonstrate that piFISTA and piFISTA-BN significantly outperform FISTA, pFISTA, iFISTA, and iFISTA-BN considering standard objective metrics such as peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM). Further, we demonstrate empirically that the proposed algorithms converge faster than the state-of-the-art techniques. © 2020 IEEE.

Item Type:	Conference Paper
Publication:	Proceedings - International Conference on Image Processing, ICIP
Publisher:	IEEE Computer Society
Additional Information:	cited By 0; Conference of 2020 IEEE International Conference on Image Processing, ICIP 2020 ; Conference Date: 25 September 2020 Through 28 September 2020; Conference Code:165772
Keywords:	Discrete wavelet transforms; Image analysis; Image reconstruction; Iterative methods; Signal to noise ratio, Image deblurring; Image deblurring problems; Objective metrics; Optimization problems; Peak signal to noise ratio; Soft-thresholding algorithm; State-of-the-art techniques; Structural similarity indices, Image enhancement
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	20 Jan 2021 06:00
Last Modified:	20 Jan 2021 06:00
URI:	http://eprints.iisc.ac.in/id/eprint/67732

Actions (login required)

View Item