Methods for and devices thereof for generating a denoised data set

A data set denoising computing device, comprising memory comprising programmed instructions stored thereon and one or more processors configured to execute the stored programmed instructions to:

• apply a Haar wavelet transform to the data set to generate a wavelet transformed data set comprising a plurality of sum values for consecutive pairs of intensities and a second data subset comprising a plurality of difference values for consecutive pairs of intensities;
• denoise the wavelet transformed data set using a thresholding rule based on comparing each of the difference values to corresponding sum values, to determine if the difference values are statistically significant based on the corresponding sum values, to remove the Poisson noise from the signal;
• and
• apply a reverse Haar wavelet transform to the denoised wavelet transformed data set to generate the denoised data set.

A non-transitory computer readable medium having stored thereon instructions for denoising a data set comprising executable code that, when executed by one or more processors, causes the processors to:

• apply a Haar wavelet transform to the data set to generate a wavelet transformed data set comprising a plurality of sum values for consecutive pairs of intensities and a second data subset comprising a plurality of difference values for consecutive pairs of intensities;
• denoise the wavelet transformed data set using a thresholding rule based on comparing each of the difference values to corresponding sum values, to determine if the difference values are statistically significant based on the corresponding sum values, to remove the Poisson noise from the signal;
• and
• apply a reverse Haar wavelet transform to the denoised wavelet transformed data set to generate the denoised data set.