A quantitative comparison of edge-preserving smoothing techniques

Abstract Edge-preserving smoothing techniques are compared by considering a test image which contains a central disk-shaped region with a step or a ramp edge against a uniform background. Free parameters are the amplitude of Gaussian noise added, the edge slope and the number of filtering iterations. The quantitative comparison measure is the normalised squared error between the filtered noisy image and the noise-free image, on the uniform image regions and on the transition region separately. The filters considered are analysed with respect to their performance under variations in the free parameters and their computer-time consumption. Results obtained are compared with published data available.

[1]  Jong-Sen Lee,et al.  Digital image smoothing and the sigma filter , 1983, Comput. Vis. Graph. Image Process..

[2]  Yrjö Neuvo,et al.  FIR-median hybrid filters , 1987, IEEE Trans. Acoust. Speech Signal Process..

[3]  M. Spann,et al.  Adaptive Gaussian weighted filtering for image segmentation , 1988, Pattern Recognit. Lett..

[4]  Azriel Rosenfeld,et al.  Iterative Enhancemnent of Noisy Images , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  M. Nagao,et al.  Edge preserving smoothing , 1979 .

[6]  Tor Lønnestad.  Connected filters for noise removal , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[7]  Roland T. Chin,et al.  Quantitative evaluation of some edge-preserving noise-smoothing techniques , 1983, Comput. Vis. Graph. Image Process..

[8]  Jitendra Malik,et al.  A network for multiscale image segmentation , 1988, 1988., IEEE International Symposium on Circuits and Systems.

[9]  Gary Mastin,et al.  Adaptive filters for digital image noise smoothing: An evaluation , 1985, Comput. Vis. Graph. Image Process..

[10]  Jong-Sen Lee,et al.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  David C. Wang,et al.  Gradient inverse weighted smoothing scheme and the evaluation of its performance , 1981 .