• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Image deblurring via adaptive proximal conjugate gradient method

Vol. 9, No. 11, November 29, 2015
10.3837/tiis.2015.11.020, Download Paper (Free):

Abstract

It is not easy to reconstruct the geometrical characteristics of the distorted images captured by the devices. One of the most popular optimization methods is fast iterative shrinkage/ thresholding algorithm. In this paper, to deal with its approximation error and the turbulence of the decrease process, an adaptive proximal conjugate gradient (APCG) framework is proposed. It contains three stages. At first stage, a series of adaptive penalty matrices are generated iterate-to-iterate. Second, to trade off the reconstruction accuracy and the computational complexity of the resulting sub-problem, a practical solution is presented, which is characterized by solving the variable ellipsoidal-norm based sub-problem through exploiting the structure of the problem. Third, a correction step is introduced to improve the estimated accuracy. The numerical experiments of the proposed algorithm, in comparison to the favorable state-of-the-art methods, demonstrate the advantages of the proposed method and its potential.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
H. Pan, Z. Jing, M. Li and P. Dong, "Image deblurring via adaptive proximal conjugate gradient method," KSII Transactions on Internet and Information Systems, vol. 9, no. 11, pp. 4604-4622, 2015. DOI: 10.3837/tiis.2015.11.020.

[ACM Style]
Han Pan, Zhongliang Jing, Minzhe Li, and Peng Dong. 2015. Image deblurring via adaptive proximal conjugate gradient method. KSII Transactions on Internet and Information Systems, 9, 11, (2015), 4604-4622. DOI: 10.3837/tiis.2015.11.020.