earticle

영어

This paper presents signal decimation and interpolation techniques under a multiresolution frame work for both lower and higher dimensional applications. New classes of non-linear basis functions have been derived from the sigmoid activation function extensively used in artificial neural networks (ANN). It has been shown that the proposed non-linear basis functions are well suited for interpolation/approximation of band limited signals. An efficient scheme for band limited signal interpolation has been introduced. Fast IIR digital filters (inverse filters) have been derived from the combinatorial theory in connection with the proposed basis functions. The proposed inverse filters can easily be implemented recursively with three multiplications and additions only. Further, the factorization of higher order filters for easy implementation has also been considered. Frequency response characteristics for the pre-filters and their corresponding interpolators are presented to reveal the quality of interpolation. An experiment has been carried out to interpolate a discrete sequence of length 33 into a sequence of length 257 (with a zooming factor of 8). Second part of the paper presents another efficient scheme for image decimation and interpolation. Experimental results on image data compression have been presented to justify the use of the proposed technique.