Patch-based image despeckling using low-rank hankel matrix approach with speckle level estimation

Hansol Kim, Paul Oh, Sangyoon Lee, Moon G.I. Kang

Research output: Contribution to journalConference articlepeer-review


In this study, we propose an image despeckling method based on low-rank Hankel matrix approach and speckle level estimation. Annihilating filter-based low-rank Hankel matrix, so called ALOHA approach is very useful to various areas, such as image inpainting and impulse noise reduction. The proposed method utilizes this approach because it provides high performance in completing irregularly subsampled images. Speckled image are subsampled using patch-based speckle level estimator which selects pixels with low speckle level and abandon the others. The subsampled image is reconstructed using low-rank structured matrix completion. Our experimental results demonstrate that precisely estimated speckle level improves despeckling performance significantly. The accuracy of the proposed speckle estimator validates better despeckling performance of the proposed method compared with conventional despeckling methods.

Original languageEnglish
Article numberIPAS-252
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Issue number11
Publication statusPublished - 2019 Jan 13
Event17th Image Processing: Algorithms and Systems Conference, IPAS 2019 - Burlingame, United States
Duration: 2019 Jan 132019 Jan 17

Bibliographical note

Publisher Copyright:
© 2019, Society for Imaging Science and Technology.

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics


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