Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Image denoising using the ridgelet bi-frame

Not Accessible

Your library or personal account may give you access

Abstract

We are concerned with the performance evaluation of the ridgelet bi-frame for image denoising application. The ridgelet bi-frame is a new (as far as we know) bi-frame system that can efficiently deal with straight singularities in two dimensions. We show that, for images dominated by straight edges, the ridgelet bi-frame can obtain much better restoration results than wavelet systems. We also investigate the statistical properties of the ridgelet bi-frame coefficients of these images. Results indicate that the marginal distribution of ridgelet bi-frame coefficients has higher kurtosis than that of wavelet coefficients of the same images. We describe a simple method through which statistical denoising algorithms previously developed in the wavelet domain can be conveniently introduced into the ridgelet bi-frame domain. In addition, we use the ridgelet bi-frame to construct another new bi-frame system referred to as the curvelet bi-frame, which can be viewed as a generalized version of the curvelet. Experiment results show that the simple hard-threshold procedure in the curvelet bi-frame domain produces restoration results comparable with those due to the state-of-the-art denoising methods.

© 2006 Optical Society of America

Full Article  |  PDF Article
More Like This
Automated defect detection system using wavelet packet frame and Gaussian mixture model

Soo Chang Kim and Tae Jin Kang
J. Opt. Soc. Am. A 23(11) 2690-2701 (2006)

High resolution image acquisition from magnetic resonance and computed tomography scans using the curvelet fusion algorithm with inverse interpolation techniques

Fatma E. Ali, Ibrahim M. El-Dokany, Abdelfattah A. Saad, Waleed Al-Nuaimy, and Fathi E. Abd El-Samie
Appl. Opt. 49(1) 114-125 (2010)

Multiresolution phase retrieval in the Fresnel region by use of wavelet transform

Alexei Souvorov, Tetsuya Ishikawa, and Armen Kuyumchyan
J. Opt. Soc. Am. A 23(2) 279-287 (2006)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (9)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (6)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (25)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved