움직임영역을 고려한 연속영상 초해상도 영상 복원
Consecutive-Frame Super-Resolution considering Moving Object Region
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In this paper, we propose a consecutive-frame super-resolution method to tackle a moving object problem. The super-resolution is a method restoring a high resolution image from a low resolution image. The super-resolution is classified into two types, briefly, single-frame super-resolution and consecutive-frame super-resolution. Typically, the consecutive-frame super-resolution recovers a better than the single-frame super-resolution, because it use more information from consecutive frames. However, the consecutive-frame super-resolution failed to recover the moving object. Therefore, we proposed an improved method via moving object detection. Experimental results showed that the proposed method restored both the moving object and the background properly.
Abstract
In this paper, we propose a consecutive-frame super-resolution method to tackle a moving object problem. The super-resolution is a method restoring a high resolution image from a low resolution image. The super-resolution is classified into two types, briefly, single-frame super-resolution and consecutive-frame super-resolution. Typically, the consecutive-frame super-resolution recovers a better than the single-frame super-resolution, because it use more information from consecutive frames. However, the consecutive-frame super-resolution failed to recover the moving object. Therefore, we proposed an improved method via moving object detection. Experimental results showed that the proposed method restored both the moving object and the background properly.
참고문헌 (18)
- S. Farsiu, "Fast and Robust Super-Resolution", IEEE Transactions on Image Processing, 13(10), pp.1327~1344 (2004)
- L. Zhang, "An Edge-Guided Image Interpolation Algorithm via Directional Filtering and Data Fusion", IEEE Transactions on Image Processing, 15(8), pp.2226~2238 (2006)
- A. Giachetti, "Real-Time Artifact-Free Image Upscaling", IEEE Transactions on Image Processing, 20(10), pp.2760~2768 (2011)
- D. Zhou, "Image zooming using directional cubic convolution interpolation", IET Image Processing, 6(6), pp.627~634 (2012)
- Gholamreza Anbarjafari, "Image Super Resolution Based on Interpolation of Wavelet Domain High Frequency Subbands and the Spatial Domain Input Image", ETRI Journal, 32(3), pp.390~394 (2010), 한국전자통신연구원
- J. M. Lee, "Super-resolution Image Reconstruction by High-frequency Components Estimation Based on Self-reference", Ph. D, pp.2015
- W. T. Freeman, "Example-Based Super-Resolution", IEEE Computer Graphics and Applications, 22(2), pp.56~65 (2002)
- 신현학, "번호판 화질 개선을 위한 국부 블록 학습 기반의 초해상도 복원 알고리즘", 한국컴퓨터정보학회논문지, 16(6), pp.71~78 (2011), 한국컴퓨터정보학회
- C. Dong, "Learning a Deep Convolutional Network for Image Super-Resolution", European Conference on Computer Vision, pp.184~199 (2014)
- H. Shen, "A MAP Approach for Joint Motion Estimation, Segmentation, and Super Resolution", IEEE Transactions on Image Processing, 16(2), pp.479~490 (2007)
- D. Mitzel, "Video Super Resolution using Duality Based TV-L1 Optical Flow", Joint Pattern Recognition Symposium, pp.432~441 (2009)
- X. Li, "A multi-frame image super-resolution method", Signal Processing, 90(2), pp.405~414 (2010)
- M. M. Islam, "Super-Resolution Enhancement Technique for Low Resolution Video", IEEE Transactions on Consumer Electronics, 56(2), pp.919~924 (2010)
- 송태엽, "번호판 인식 향상을 위한 번호판 검출과 초해상도 융합 방법", 한국컴퓨터정보학회논문지, 16(4), pp.55~62 (2011), 한국컴퓨터정보학회
- C. Liu, "A Bayesian Approach to Adaptive Video Super Resolution", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.209~216 (2011)
- Z. Ma, "Handling motion blur in multi-frame super-resolution", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.5224~5232 (2015)
- W. Shi, "Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.1874~1883 (2016)
- B. D. Lucas, "An iterative image registration technique with and application to stereo vision", International Joint Conference on Artificial Intelligence, 81(1), pp.674~694 (1981)