DOI QR코드

DOI QR Code

Objective Quality Assessment Method for Stitched Images

스티칭 영상의 객관적 영상화질의 평가 방법

  • Billah, Meer Sadeq (Seoul National University of Science and Technology, Department of Electrical and Information Engineering) ;
  • Ahn, Heejune (Seoul National University of Science and Technology, Department of Electrical and Information Engineering)
  • Received : 2017.12.29
  • Accepted : 2018.03.08
  • Published : 2018.03.30

Abstract

Recently, stitching techniques are used for obtaining wide FOV, e.g., panorama contents, from normal cameras. Despite many proposed algorithms, the no objective quality evaluation method is developed, so the comparison of algorithms are performed only in subjective way. The paper proposes a 'Delaunay-triangulation based objective assessment method' for evaluating the geometric and photometric distortions of stitched or warped images. The reference and target images are segmented by Delaunay-triangulation based on matched points between two images, the average Euclidian distance is used for geometric distortion measure, and the average or histogram of PSNR for photometric measure. We shows preliminary results with several test images and stitching methods for demonstrate the benefits and application.

이미지 스티칭 기술은 일반 카메라로부터 촬영된 영상을 파노라마와 같이 넓은 화각(Field of View)으로 만들어주는 기술이다. 약 20년정도 연구되어 왔으며, 최근에 특히 상용화 시스템들이 소개되고 있다. 그러나, 많은 제안 된 알고리즘에도 불구하고 객관적인 품질 평가 방법이 개발되지 않았으므로 알고리즘의 비교는 거의 주관적인 방식으로 만 수행되었다. 이 논문은 스티칭 또는 뒤틀린 이미지의 기하학적 및 광도 측정 왜곡을 평가하기위한 Delaunay 삼각분할방식을 사용하여 객관적 평가 방법을 제안한다. 기준 이미지와 대상 이미지는 두 이미지 사이의 일치 지점을 기반으로 하는 델라 네이 - 삼각 측량에 의해 세그먼트 화되고, 평균 유클리드 거리가 기하학적 왜곡 측정에 사용되며, 측광 측정을 위한 PSNR의 평균 또는 막대 그래프가 사용됩니다. 우리는 몇 가지 테스트 이미지와 스티칭 방법을 통해 예비 결과를 보여줌으로써 이점과 적용을 입증한다.

Keywords

References

  1. D. Ghosh, N. Kaabouch, "A survey on image mosaicing techniques," Journal of Visual Communication and Image Representation, Vol. 34, No.1, pp. 1-11, January, 2016. https://doi.org/10.1016/j.jvcir.2015.10.014
  2. P. Topiwala, W. Dai, M. Krishnan, A. Abbas, A. S. Doshi, D. Newman, "Performance comparison of AV1, HEVC, and JVET video codecs on 360 (spherical) video," Applications of Digital Image Processing XL, Vol. 10396, p. 1039609, September, 2017.
  3. R. Szeliski, "Image alignment and stitching: A tutorial. Foundations and Trends," Computer Graphics and Vision, Vol 2, No. 1, pp. 1-104. 2006. https://doi.org/10.1561/0600000009
  4. Brown, M., & Lowe, D. G. (2007). Automatic panoramic image stitching using invariant features. International journal of computer vision, 74(1), 59-73. https://doi.org/10.1007/s11263-006-0002-3
  5. R. Hartley, A Zisserman, "Multiple View Geometry in Computer Vision," 2nd Ed., Cambridge Press, New York, NY, USA. February, 2003.
  6. F. Dornaika, R. Chung, "Mosaicking images with parallax," Signal Processing: Image Communication, Vol. 19, No. 8, pp. 771-786, 2004. https://doi.org/10.1016/j.image.2004.06.008
  7. A. Eden, M. Uyttendaele, R. Szeliski, "Seamless image stitching of scenes with large motions and exposure differences. In Computer Vision and Pattern Recognition, New York, NY, USA, pp. 2498-2505. 2006.
  8. J. Zaragoza, T. J. Chin, M. S. Brown, D. Suter, "As-projective-as-possible image stitching with moving DLT," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Portland, Oregon, USA, pp. 2339-2346, 2013
  9. C. H. Chang, Y. Sato, Y. Y. Chuang. "Shape-preserving half-projective warps for image stitching," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, Ohio, USA pp. 3254-3261, 2014.
  10. Qureshi, H. S., Khan, M. M., Hafiz, R., Cho, Y., & Cha, J. (2012). Quantitative quality assessment of stitched panoramic images. IET Image Processing, 6(9), 1348-1358. https://doi.org/10.1049/iet-ipr.2011.0641
  11. Wu, Y. "test Image for Image Stitching, available on https://github.com/ppwwyyxx/OpenPano
  12. V. Pham, "test images for Image stitching, available on https://github.com/phvu/misc/tree/master/imageStitch
  13. Delaunay, Boris. "Sur la sphere vide." Izv. Akad. Nauk SSSR, Otdelenie Matematicheskii i Estestvennyka Nauk 7.793-800 (1934): 1-2.