Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Edge Preserving Smoothing in Infrared Image using Relativity of Guided Filter

  • Kim, Il-Ho (Dept. of Electro-Optronics 2Team, Hanwha Systems Co.)
  • Received : 2018.10.30
  • Accepted : 2018.11.21
  • Published : 2018.12.31
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Abstract

In this paper, we propose an efficient edge preserving smoothing filter for Infrared image that can reduce noise while preserving edge information. Infrared images suffer from low signal-to-noise ratio, low edge detail information and low contrast. So, detail enhancement and noise reduction play crucial roles in infrared image processing. We first apply a guided image filter as a local analysis. After the filtering process, we optimization globally using relativity of guided image filter. Our method outperforms the previous methods in removing the noise while preserving edge information and detail enhancement.

Keywords

CPTSCQ_2018_v23n12_27_f0001.png 이미지

Fig. 1. Compare edge preserving smoothing on an Infrared Image with gaussian noise. (a) Input Image. (b) Gaussian noise added. (c) Bitonic. (d) GIF. (e) RTV. (f) WLS. (g) RoG. (h) RoGIF

CPTSCQ_2018_v23n12_27_f0002.png 이미지

Fig. 2. Compare edge preserving smoothing on an Infrared Image with gaussian noise. (a) Input Image. (b) Gaussian noise added. (c) Bitonic. (d) GIF. (e) RTV. (f) WLS. (g) RoG. (h) RoGIF

CPTSCQ_2018_v23n12_27_f0003.png 이미지

Fig. 3. Compare detail enhancement on an Infrared Image. (a),(e),(i) Bitonic. (b),(f),(j) RTV. (c),(g),(k) RoG. (d),(h),(i) RoGIF

CPTSCQ_2018_v23n12_27_f0004.png 이미지

Fig. 4. Detail enhancement (a) Coarse detail boost, (b) Fine detail boost, (c) Combine Coarse and Fine detail

Table 1. Algorithm of RoGIF

CPTSCQ_2018_v23n12_27_t0001.png 이미지

Table 2. PSNR, SSIM values for Fig. 1,2.

CPTSCQ_2018_v23n12_27_t0002.png 이미지

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