Abstract: A machine-implemented method for computerized digital signal processing obtains a digital signal from data storage or from conversion of an analog signal and determines, from the digital signal, Measuring Matrices (MM). Each measuring matrix has a plurality of cells, each cell having an amplitude corresponding to the signal energy in a frequency bin for a time slice. Cells in each measuring matrix having maximum amplitudes within a time slice are identified as maximum cells. Maxima that coincide in time and frequency are identified and a correlated maxima matrix (PMM) is constructed showing the coinciding maxima and the adjacent marked maxima are linked into partial chains. If only one MM is constructed, multiple types of maxima are identified to generate the (PMM). The partial chains are isolated by parameters for a single domain or multiple domains to identify partial chains and possible separation of complex compound waveforms in the digital signal.

Abstract: A machine/computer implemented system, method, and computer program product for scored pixel intensity value adjustment of a digital image is disclosed. The system is configured to obtain a digital image from data storage and perform pixel-by-pixel comparisons to generate per pixel scores. The types of comparisons include discovering minima and maxima per pixel scores by comparing to neighboring non-adjacent pixel pairs, delta pair scores by comparing to neighboring pixels, and multiple vector score types by comparing to vectors made up of individual pixels. This new information is applied to adjust each pixel's value. The system is further configured to generate a collection of such scores for a plurality of pixels in a digital image and to generate a multi-dimensional scored pixel adjusted image. The scored pixel adjustment yields a new digital image, wherein the value of a given pixel is adjusted based on one or more of the score types.

Abstract: A machine/computer implemented system, method, and computer program product for scored pixel intensity value adjustment of a digital image is disclosed. The system is configured to obtain a digital image from data storage and perform pixel-by-pixel comparisons to generate per pixel scores. The types of comparisons include discovering minima and maxima per pixel scores by comparing to neighboring non-adjacent pixel pairs, delta pair scores by comparing to neighboring pixels, and multiple vector score types by comparing to vectors made up of individual pixels. This new information is applied to adjust each pixel's value. The system is further configured to generate a collection of such scores for a plurality of pixels in a digital image and to generate a multi-dimensional scored pixel adjusted image. The scored pixel adjustment yields a new digital image, wherein the value of a given pixel is adjusted based on one or more of the score types.

Abstract: A machine-implemented method for computerized digital signal processing obtains a digital signal from data storage or from conversion of an analog signal and determines, from the digital signal, Measuring Matrices (MM). Each measuring matrix has a plurality of cells, each cell having an amplitude corresponding to the signal energy in a frequency bin for a time slice. Cells in each measuring matrix having maximum amplitudes within a time slice are identified as maximum cells. Maxima that coincide in time and frequency are identified and a correlated maxima matrix (PMM) is constructed showing the coinciding maxima and the adjacent marked maxima are linked into partial chains. If only one MM is constructed, multiple types of maxima are identified to generate the (PMM). The partial chains are isolated by parameters for a single domain or multiple domains to identify partial chains and possible separation of complex compound waveforms in the digital signal.