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

  • 제24권6호
  • /
  • Pages.73-80
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  • 2019
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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Adaptive local histogram modification method for dynamic range compression of infrared images

  • 투고 : 2019.05.04
  • 심사 : 2019.06.08
  • 발행 : 2019.06.28
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초록

In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

키워드

CPTSCQ_2019_v24n6_73_f0001.png 이미지

Fig. 1. Histogram modification

CPTSCQ_2019_v24n6_73_f0002.png 이미지

Fig. 2. Six types of block

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Fig. 3. overlapped block

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Fig. 4. Result of block classification (a) image (b) classification result

CPTSCQ_2019_v24n6_73_f0005.png 이미지

Fig. 5. Histogram modification of blocks (a) Histogram modification of Fig.1.(a)(b) Histogram modification of Fig.1.(d) (c) Histogram modification of Fig.1.(f)

CPTSCQ_2019_v24n6_73_f0006.png 이미지

Fig. 6. Result of dynamic range compression

CPTSCQ_2019_v24n6_73_f0007.png 이미지

Fig. 8. Result image (a) Original image (b) HE (c) PHE (d) GHM (e) CLAHE (f) Proposed algorithm

CPTSCQ_2019_v24n6_73_f0008.png 이미지

Fig. 9. Result image (a) Original image (b) HE (c) PHE (d) GHM (e) CLAHE (f) Proposed algorithm

CPTSCQ_2019_v24n6_73_f0009.png 이미지

Fig. 10. Result image (a) CLAHE (b) Proposed algorithm

CPTSCQ_2019_v24n6_73_f0010.png 이미지

Fig. 7. (a) Example of block artifact (b) Result of reduction block artifact

Table 1. Value of Entropy

CPTSCQ_2019_v24n6_73_t0001.png 이미지

참고문헌

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