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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.8 No.6
- 발행연도
- 2019.12
- 수록면
- 423 - 430 (8page)
- DOI
- 10.5573/IEIESPC.2019.8.6.423
이용수
초록· 키워드
오류제보하기
This paper proposes a method for accelerating deep learning based super-resolution technology. In order to alleviate the complexity of the deep learning based super-resolution technology, the proposed method extracts the horizontal and vertical high-frequency signals separately using one-dimensional filters. Then, the final super-resolution image is obtained by the proposed network from the horizontal and vertical high-frequency signals and the low-resolution input image. The proposed method requires a low computational complexity by using only onedimensional filters due to a smaller number of weights. The proposed method in the high-resolution image restoration experiment shows that the average visual quality in PSNR and SSIM is comparable to ones of VDSR. However, the average speed performance is accelerated by 86.57%.
목차
Abstract
1. Introduction
2. Conventional CNN-based Superresolution Algorithms
3. Proposed 1D CNN Super Resolution Algorithm
4. Experimental Results and Discussion
5. Conclusion
References
참고문헌 (19)
참고문헌 신청
S. C. Park / 2003 / Superresolution image reconstruction: a technical overview / IEEE Signal Processing Magazine 20(3):21~36
Oh-Young Lee / 2014 / Multi-frame super-resolution of high frequency with spatially weighted bilateral total variance regularization / IEIE Transactions on Smart Processing & Computing 3(3):271~274
Sangsik Jang / 2012 / Image processing-based validation of unrecognizable numbers in severely distorted license plate images / IEIE Transactions on Smart Processing & Computing 1(1):17~26
C. M. B. Michael / 2003 / advances in neural information processing systems 15 / The MIT Press :1303~1310
J. Tian / 2005 / An MCMC approach for bayesian super-resolution image reconstruction / IEEE International Conference on Image Processing 2005
Oh-Young Lee / 2014 / Multi-frame super-resolution of high frequency with spatially weighted bilateral total variance regularization / IEIE Transactions on Smart Processing & Computing 3(3):271~274
Sangsik Jang / 2012 / Image processing-based validation of unrecognizable numbers in severely distorted license plate images / IEIE Transactions on Smart Processing & Computing 1(1):17~26
C. M. B. Michael / 2003 / advances in neural information processing systems 15 / The MIT Press :1303~1310
J. Tian / 2005 / An MCMC approach for bayesian super-resolution image reconstruction / IEEE International Conference on Image Processing 2005
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