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author:

Zhao, Di (Zhao, Di.) [1] | Ma, Lan (Ma, Lan.) [2] | Lin, Zhixian (Lin, Zhixian.) [3] (Scholars:林志贤) | Guo, Tailiang (Guo, Tailiang.) [4] (Scholars:郭太良) | Lin, Shanling (Lin, Shanling.) [5]

Indexed by:

CPCI-S

Abstract:

When taking pictures in extremely dark light, the image taken is usually very dark and noisy due to the small amount of light entering, and there is clear distortion of color. Since the method of using multi-frame or long-exposure has limitations, we use the single-frame denoising method based on residual dense network (RDN), which uses residual dense block (ROB) to makes full use of local features. Our method has achieved better results than state-of-the-art methods. In addition, we have applied the trained model without line-tuning on photos captured by different cameras and have obtained similar end-to-end enhancements.

Keyword:

dark-scene image denoise image enhancing residual dense block residual dense network

Community:

  • [ 1 ] [Zhao, Di]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou, Peoples R China
  • [ 2 ] [Lin, Zhixian]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou, Peoples R China
  • [ 3 ] [Guo, Tailiang]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou, Peoples R China
  • [ 4 ] [Lin, Shanling]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou, Peoples R China
  • [ 5 ] [Ma, Lan]TCL Corp Res, Hong Kong, Peoples R China

Reprint 's Address:

  • 林志贤

    [Lin, Zhixian]Fuzhou Univ, Coll Phys & Informat Engn, Fuzhou, Peoples R China

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Source :

2019 8TH INTERNATIONAL SYMPOSIUM ON NEXT GENERATION ELECTRONICS (ISNE)

ISSN: 2378-8593

Year: 2019

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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