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author:

Li, Jun (Li, Jun.) [1] | Han, Yuxuan (Han, Yuxuan.) [2] | Gao, Yin (Gao, Yin.) [3] | Li, Qiming (Li, Qiming.) [4] | Wang, Sumei (Wang, Sumei.) [5]

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Abstract:

In image processing, edge-preserving image smoothing methods that maintain weak structure while smoothing multiscale textures with strong gradients remain challenging. In this paper, a new global optimization method named Enhance Relative Total Variation Embedded with Bilateral Filtering is proposed. The texture and structure are intuitively considered separately from the model generalization. First, the weak structures are separated from the over-penalized texture and structure items by embedding bilateral filtering. Then, the in-set shrinking edges/structures are gradually recovered by constructing a contrast stretching function. In comparison to current state-of-the-art methods, experimental results demonstrate that the method is effective in maintaining weak structures and suppressing multiscale textures. © 2023 IEEE.

Keyword:

Deep learning Edge detection E-learning Global optimization Image enhancement Nonlinear filtering

Community:

  • [ 1 ] [Li, Jun]Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China, Quanzhou Institute of Equipment Manufacturing, Chinese Academy of Sciences, Quanzhou; 362200, China
  • [ 2 ] [Han, Yuxuan]Department of Electronic Information, School of Advanced Manufacturing, Fuzhou University, Quanzhou; 350002, China
  • [ 3 ] [Han, Yuxuan]Quanzhou Institute of Equipment Manufacturing, Chinese Academy of Sciences, Quanzhou; 362200, China
  • [ 4 ] [Gao, Yin]Fujian Institute of Research on the Structure of Matter, University of Chinese Academy of Sciences, Beijing; 101408, China
  • [ 5 ] [Li, Qiming]Quanzhou Institute of Equipment Manufacturing, Chinese Academy of Sciences, Quanzhou; 362200, China
  • [ 6 ] [Wang, Sumei]Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, Hong Kong
  • [ 7 ] [Wang, Sumei]National Rail Transit Electrification and Automation Engineering Technology Research Center (Hong Kong Branch), Hong Kong

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Source :

IEEE Transactions on Circuits and Systems for Video Technology

ISSN: 1051-8215

Year: 2023

Issue: 10

Volume: 33

Page: 5420-5432

8 . 3

JCR@2023

8 . 3 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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