IMAGE SMOOTHING WITH EXPONENTIAL FUNCTIONS
Mitra Basu, Min Su · International Journal of Pattern Recognition and Artificial Intelligence · 2001
Noise reduction in images, also known as image smoothing, is an essential and first step before further processings of the image. The key to image smoothing is to preserve important features while removing noise from the image. Gaussian function is widely used in image smoothing. Recently it has been reported that exponential functions (value of the exponent is not equal to 2) perform substantially better than Gaussian functions in modeling and preserving image features. In this paper we propose a family of exponential functions, that include Gaussian when the value of the exponent is 2, for image smoothing. We experiment with a variety of images, artificial and real, and demonstrate that optimal results are obtained when the value of the exponent is within a certain range.