SUSAN—A New Approach to Low Level Image Processing
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This paper describes a new approach to low level image processing; in particular, edge and corner detection and structure preserving noise reduction.
Non-linear filtering is used to define which parts of the image are closely related to each individual pixel; each pixel has associated with it a local image region which is of similar brightness to that pixel. The new feature detectors are based on the minimization of this local image region, and the noise reduction method uses this region as the smoothing neighbourhood. The resulting methods are accurate, noise resistant and fast.
Details of the new feature detectors and of the new noise reduction method are described, along with test results.
- Akarun, L. and Haddad, R. 1992. Adaptive decimated median filtering. Pattern Recognition Letters, 13: 57-62.
- Arce, G. R. and Fontana, S. A. 1988. On the midrange estimator. IEEE Trans. on Acoustics, Speech and Signal Processing, ASSP-36: 920-922.
- Beaudet, P. R. 1978. Rotational invariant image operators. In Proc. of the Int. Conf. on Pattern Recognition, pp. 579-583.
- Bedner, J. B. and Watt, T. L. 1984. Alpha-trimmed means and their relationships to median filters. IEEE Trans. on Acoustics, Speech and Signal Processing, ASSP-32: 145-153.
- Blake, A. and Zisserman, A. 1987. Visual Reconstruction. MIT Press: Cambridge, USA.
- Brownrigg, D. R. K. 1984. The weighted median filter. Commun. ACM, 27: 807-818.
- Canny, J. F. 1983. Finding Edges and Lines in Images. Master's thesis, MIT, Cambridge, USA.
- Canny, J. F. 1986. A computational approach to edge detection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6): 679- 698.
- Charnley, D. and Blissett, R. J. 1989. Surface reconstruction from outdoor image sequences. Image and Vision Computing, 7(1): 10-16.
- Chin, R. T. and Yeh, C.-L. 1983. Quantitative evaluation of some edge-preserving noise-smoothing filters. Computer Vision, Graphics and Image Processing, 23: 67-91.
- Davis, L. S. and Rosenfeld, A. 1978. Noise cleaning by iterated local averaging. IEEE Trans. on Systems, Man and Cybernetics, SMC-8(9): 705-710.
- Deriche, R. 1987. Using Canny's criteria to derive a recursively implemented optimal edge detector. Int. Journal of Computer Vision, 1(2): 167-187.
- Deriche, R. and Giraudon, G. 1990. Accurate corner detection: An analytical study. In Proc. 3rd Int. Conf. on Computer Vision, pp. 66-70.
- Dreschler, L. and Nagel, H.-H. 1981. Volumetric model and 3D trajectory of a moving car derived from monocular TV-frame sequence of a street scene. Computer Vision, Graphics and Image Processing, 20(3): 199-228.
- Ehrich, R. 1978. A symmetric hysteresis smoothing algorithm that preserves principal features. Computer Graphics and Image Processing, 8: 121-126.
- Förstner, W. and Gülch, E. 1987. A fast operator for detection and precise location of distinct points, corners and centres of circular features. In ISPRS Intercommission Workshop, Interlaken, pp. 149-155.
- Geiger, D. and Girosi, F. 1990. Parallel and deterministic algorithms from MRFs: Surface reconstruction and integration. In Proc. 1st European Conf. on Computer Vision, pp. 89-98.
- Haralick, R. M. 1984. Digital step edges from zero crossing of second directional derivatives. IEEE Trans. on Pattern Analysis and Machine Intelligence, 6(1): 58-68.
- Haralick, R. M. and Shapiro, L. G. 1992. Computer and Robot Vision. Addison-Wesley, Vol. 1.
- Harris, C. G. and Pike, J. M. 1988a. 3D positional integration from image sequences. Image and Vision Computing, 6(2): 87- 90.
- Harris, C. G. and Stephens, M. 1988b. A combined corner and edge detector. In 4th Alvey Vision Conference, pp. 147-151.
- Harwood, D., Subbarao, M., Hakalahti, H., and Davis, L. S. 1987. A new class of edge-preserving smoothing filters. Pattern Recognition Letters, 6: 155-162.
- Hueckel, M. H. 1971. An operator which locates edges in digitized pictures. Journal of the Association for Computing Machinery, 18(1): 113-125.
- Kitchen, L. and Rosenfeld, A. 1982. Gray-level corner detection. Pattern Recognition Letters, 1: 95-102.
- Lee, J.-S. 1983. Digital image smoothing and the sigma filter. Computer Vision, Graphics and Image Processing, 24: 255-269.
- Lev, A., Zucker, S. W., and Rosenfeld, A. 1977. Iterative enhancement of noisy images. IEEE Trans. on Systems, Man and Cybernetics, 7: 435-442.
- Liu, S.-T. and Tsai, W.-H. 1990. Moment-preserving corner detection. Pattern Recognition, 23: 441-460.
- Marr, D. and Hildreth, E. C. 1980. Theory of edge detection. Proc. Roy. Soc. London., Vol. B-207, pp. 187-217.
- McDonnell, M. J. 1981. Box-filtering techniques. Computer Graphics and Image Processing, 17: 65-70.
- Medioni, G. and Yasumoto, Y. 1987. Corner detection and curve representation using cubic b-splines. Computer Vision, Graphics and Image Processing, 39: 267-278.
- Mehrotra, R., Nichani, S., and Ranganathan, N. 1990. Corner detection. Pattern Recognition, 23: 1223-1233.
- Moravec, H. P. 1977. Towards automatic visual obstacle avoidance. In Proc. of the International Joint Conference on Artificial Intelligence, p. 584.
- Moravec, H. P. 1979. Visual mapping by a robot rover. In Proc. of the 6th International Joint Conference on Artificial Intelligence, pp. 598-600.
- Nagao, M. and Matsuyama, T. 1979. Edge preserving smoothing. Computer Graphics and Image Processing, 9: 394- 407.
- Nagel, H.-H. 1987. Principles of (low level) computer vision. In Fundamentals in Computer Understanding: Speech and Vision, J. P. Haton (Ed.), Cambridge University Press, pp. 113- 139.
- Noble, J. A. 1989. Descriptions of Image Surfaces. D. Phil. Thesis, Robotics Research Group, Department of Engineering Science, Oxford University.
- Nordström, N. 1990. Biased anisotropic diffusion-A unified regularization and diffusion approach to edge detection. In Proc. 1st European Conf. on Computer Vision, pp. 18- 27.
- Paler, K., Föglein, J., Illingworth, J., and Kittler, J. 1984. Local ordered grey levels as an aid to corner detection. Pattern Recognition, 17(5): 535-543.
- Perona, P. and Malik, J. 1987. Scale space and edge detection using anisotropic diffusion. In IEEE Workshop on Computer Vision, pp. 16-22.
- Pratt, W. K. 1972. Generalized Wiener filtering computation techniques. IEEE Trans. Computers, C-21: 636-692.
- Prewitt, J. M. S. 1970. Object enhancement and extraction. Picture Processing and Psychopictorics, in B. S. Lipkin and A. Rosenfeld (Eds.), Academic Press.
- Roberts, L. G. 1965. Machine perception of three dimensional solids. In Optical and Electro-optical Information Processing, J. T. Tippet (Ed.), MIT Press, pp. 159-197.
- Rohr, K. 1992. Modelling and identification of characteristic intensity variations. Image and Vision Computing, 10(2): 66- 76.
- Saint-Marc, P., Chen, J. S., and Medioni, G. 1989. Adaptive smoothing: A general tool for early vision. In Proc. Conf. Computer Vision and Pattern Recognition, pp. 618-624.
- Scollar, I., Weidner, B., and Huang, T. S. 1984. Image enhancement using the median and the interquartile distance. Computer Vision, Graphics and Image Processing, 25: 236- 251.
- Shen, Q. 1990. Fuzzy image smoothing. In Proc. Int. Conf. on Pattern Recognition, pp. 74-78.
- Shen, J. and Castan, S. 1992. An optimal linear operator for step edge detection. Computer Vision, Graphics and Image Processing, 54(2): 112-133.
- Sinha, S. G. and Schunk, B. G. 1992. A two-stage algorithm for discontinuity-preserving surface reconstruction. IEEE Trans. on Pattern Analysis and Machine Intelligence, 14(1): 36- 55.
- Smith, S. M. 1990a. A brief quantitative assessment of a passive 3D measurement system. RARDE Memorandum 31/90, DRA Chertsey, Chobham Lane, Chertsey, Surrey, UK.
- Smith, S. M. 1990b. Extracting information from images. First year D. Phil. Report, Robotics Research Group, Department of Engineering Science, Oxford University.
- Smith, S. M. 1992. Feature Based Image Sequence Understanding. D. Phil. thesis, Robotics Research Group, Department of Engineering Science, Oxford University.
- Smith, S. M. and Brady, J. M. 1994. A scene segmenter; visual tracking of moving vehicles. Engineering Applications of Artificial Intelligence, 7(2): 191-204.
- Sobel, I. 1990. An isotropic 3 x 3 image gradient operator. Machine Vision for Three-Dimensional Scenes, H. Freeman (Ed.), Academic Press, pp. 376-379.
- Tukey, J. W. 1971. Exploratory Data Analysis. Addison-Wesley: Menlo Park, CA.
- Venkatesh, S. 1990. A Study of Energy Based Models for the Detection and Classification of Image Features. Ph. D. thesis, The University of Western Australia, Department of Computer Science.
- Venkatesh, S. and Owens, R. 1989. An energy feature detection scheme. In Proceedings, IEEE Int. Conf. on Image Processing, Singapore, pp. 553-557.
- Venkatesh, S. and Kitchen, L. J. 1992. Edge evaluation using necessary components. Computer Vision, Graphics and Image Processing, 54(1): 23-30.
- Wang, D. C. C., Vagnucci, A. H., and Li, C. C. 1981. Gradient inverse weighted smoothing scheme and the evaluation of its performance. Computer Graphics and Image Processing, 15: 167- 181.
- Wang, H. and Brady, M. 1992. Corner detection with subpixel accuracy. Technical Report OUEL 1925/92, University of Oxford.
- Witkin, A. P. 1983. Scale-space filtering. In Proc. IJCAI 1983, pp. 1019-1021.
- Zuniga, O. A. and Haralick, R. M. 1983. Corner detection using the facet model. In Proc. Conf. Computer Vision and Pattern Recognition, pp. 30-37.
- SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Volume 23, Issue 1 , pp 45-78
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