Basic image processing operations - Feature Extraction and Image Processing - page 96

level image processing (Lindley, 1991) and (Parker, 1994). Some of the more advanced
texts include more coverage of low-level operators, such as Rosenfeld and Kak (Rosenfeld,
1982) and Castleman (Castleman, 1996). Parker (1994) includes C code for nearly all the
low-level operations in this chapter. For study of the effect of the median operator on image
data, see Bovik (1987). The Truncated Median Filter is covered again in Davies (1994). For
further study of the effects of different statistical operators on ultrasound images, see
Evans (1995, 1996).

3.7 References

Baxes, G. A., Digital Image Processing, Principles and Applications , Wiley & Sons Inc.,
NY USA, 1994
Bamber, J. C. and Daft, C., Adaptive Filtering for Reduction of Speckle in Ultrasonic
Pulse-Echo Images, Ultrasonics , 24 (3), pp. 41-44, 1986
Bovik, A. C., Huang, T. S. and Munson, D. C., The Effect of Median Filtering on Edge
Estimation and Detection, IEEE Trans. on PAMI , 9 (2), pp. 181-194, 1987
Campbell, J. D., Edge Structure and the Representation of Pictures , PhD Thesis, University
Missouri, Columbia USA, 1969
Castleman, K. R., Digital Image Processing , Prentice Hall Inc., Englewood Cliffs, NJ,
USA, 1996
Davies, E. R., On the Noise Suppression Characteristics of the Median, Truncated Median
and Mode Filters, Pattern Recog. Lett. , 7 (2), pp. 87-97, 1988
Davies, E. R., Machine Vision : Theory, Algorithms and Practicalities , Academic Press,
London UK, 1990
Evans, A. N. and Nixon, M. S., Mode Filtering to Reduce Ultrasound Speckle for Feature
Extraction, Proc. IEE-Vision, Image and Signal Processing , 142 (2), pp. 87-94, 1995
Evans, A. N. and Nixon, M. S., Biased Motion-Adaptive Temporal Filtering for Speckle
Reduction in Echocardiography, IEEE Trans. Medical Imaging , 15 (1), pp. 39-50, 1996
Fairhurst, M. C., Computer Vision for Robotic Systems , Prentice Hall International (UK)
Ltd, Hemel Hempstead UK, 1988
Glasbey, C. A., An Analysis of Histogram-Based Thresholding Algorithms, CVGIP-Graphical
Models and Image Processing , 55 (6), pp. 532-537, 1993
Gonzalez, R. C. and Wintz, P., Digital Image Processing , 2nd Edition, Addison Wesley
Publishing Co. Inc., Reading, MA USA, 1987
Hearn, D. and Baker, M. P., Computer Graphics C Version , 2nd Edition, Prentice Hall, Inc.,
Upper Saddle River, NJ USA, 1997
Hodgson, R. M., Bailey, D. G., Naylor, M. J., Ng, A. and Mcneill, S. J., Properties,
Implementations and Applications of Rank Filters, Image and Vision Computing , 3 (1),
pp. 3-14, 1985
Lee, S. A., Chung, S. Y. and Park, R. H., A Comparative Performance Study of Several
Global Thresholding Techniques for Segmentation, CVGIP , 52 , pp. 171-190, 1990
Lindley, C. A., Practical Image Processing in C , Wiley & Sons Inc., NY USA, 1991
Loupas, T. and McDicken, W. N., Noise Reduction in Ultrasound Images by Digital Filtering,
British Journal of Radiology , 60 , pp. 389-392, 1987
Otsu, N., A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. on
SMC , 9 (1) pp. 62-66, 1979
Parker, J. R., Practical Computer Vision using C , Wiley & Sons Inc., NY USA, 1994