This paper describes the application of matrix convolution filters to time-of-flight matrix-assisted laser desorption mass spectra to improve the appearance of a particular spectrum and to extract peaks from poorly resolved signals. These filters are commonly used in image enhancement to sharpen blurry images and remove noise because of their general applicability and their modest requirements for calculation speed. The theory of these filters is discussed, as applied to mass spectra, and examples of spectra processed using a variety of filters are shown to demonstrate the improvements and artifacts that can be generated.
Mass spectra obtained from time-of-flight mass spectrometers with matrix-assisted laser desorption ion sources have suffered in comparison with other types of mass spectra because of their relatively low resolution and high backgrounds.' In spite of their aesthetic shortcomings, these mass spectra have become the basis of a large number of publications and have become widely accepted in the analytical and biochemical community?* Mass spectra are part of a much larger, general class of data that can be represented as a multidimensional digital array of intensity information. The most studied types of data that fit into this general classification are digital representations of optical images, which are three-dimensional arrays of two spatial coordinates and an intensity. Methods for improving the 'quality' and extracting relevant information from blurry, noisy images have become very sophisticated. Many types of data manipulation are used to improve these images. Fourier transformation of the digital data, followed by filtering and inverse transformation can be used to remove many types of noise from images! Modeldependent transformations can be used to remove predictable defects from images, such as correcting for outof-focus effects or uniform movement of an element of the image.'
Mass spectra belong to the same general class of mathematical representations as digital images of photographs except that, rather than being three-dimensional arrays { x , y, intensify}, they are two-dimensional arrays consisting of mass-to-charge ratio (rn/z) and intensity (m/z, Z). The data to be derived from the mass spectrum from a set of discrete m/z values that represent the m/z values of the ion species produced by the ion source. These m/z values are further processed by identifying the ion charge and the identity of adduct species, to produce a set of molecular mass data representing the masses of the molecular species present in the orignal sample. Some types of data processing have been traditionally applied to mass spectra, such as the subtraction of smooth or curved backgrounds and smoothing using Savitsky-Golay algorithms.6 Signals obtained from ion-cyclotron resonance mass spectrometers are only useful after they have been subjeced to very intensive image processing using Fourier transforms and related filtering techniques.' The application of model-dependent image corrections to quadrupole mass