Abstract: A noise reduction filter for data signals is implemented using two orthogonal coordinates comprising intensity and differential intensity values generated from sampling and sorting the data signals. A weighting function is used to amplify or reduce different portions of a data set distribution generated using the intensity and differential intensity values. The weighting function may also include scalar constants to further enhance the capability of the noise reduction filter. The noise reduction filter can be used to reduce the noise components or increase the useful signal components of a noisy data signal, thereby increasing the signal-to-noise ratio, and also increasing spectral resolution. The noise reduction filter can also be used in special cases where the intensity and frequency spectra of the noisy data signal are overlapping. The noise reduction filter may be used in various applications including spectroscopy and image processing, among others.

Abstract: A noise reduction filter for data signals is implemented using two orthogonal coordinates comprising intensity and differential intensity values generated from sampling and sorting the data signals. A weighting function is used to amplify or reduce different portions of a data set distribution generated using the intensity and differential intensity values. The weighting function may also include scalar constants to further enhance the capability of the noise reduction filter. The noise reduction filter can be used to reduce the noise components or increase the useful signal components of a noisy data signal, thereby increasing the signal-to-noise ratio, and also increasing spectral resolution. The noise reduction filter can also be used in special cases where the intensity and frequency spectra of the noisy data signal are overlapping. The noise reduction filter may be used in various applications including spectroscopy and image processing, among others.