Denoising of multispectral images using wavelet thresholding

In this paper a denoising technique for multispectral images exploiting interband correlations is proposed. A redundant wavelet transform is applied and denoising is applied by thresholding wavelet coefficients. A scale adaptive threshold value is obtained by exploiting the interband correlation of the signal. First, the coefficients from different bands are multiplied. For these products, the signal and noise probability density functions (pdf) become more separated. The high signal correlation between bands is exploited further by summing these products over all bands, in this way separating noise and signal pdfs even more. The noise pdf of the proposed quantities is derived analytically and from this, a wavelet threshold is derived. The technique is demonstrated to outperform single band wavelet thresholding on multispectral remote sensing images.