Abstract:
This work presents a procedure to optimize a wavelet filter in terms of discrimination capability between the classes characterizing a given hyperspectral remote sensing ...View moreMetadata
Abstract:
This work presents a procedure to optimize a wavelet filter in terms of discrimination capability between the classes characterizing a given hyperspectral remote sensing image. To this end, this procedure estimates the coefficients of the wavelet filter bank by means of a particle swarm optimization (PSO) so that to maximize the average Bhattacharyya distance. The obtained experimental results show that PSO-based optimized wavelets can significantly outperform conventional wavelets.
Date of Conference: 12-17 July 2009
Date Added to IEEE Xplore: 18 February 2010
ISBN Information: