Method for estimating parameters of a graph spectral filter using training data

摘要

A method processes a signal represented as a graph by first determining a graph spectral transform based on the graph. In a spectral domain, parameters of a graph filter are estimated using a training data set of unenhanced and corresponding enhanced signals. The graph filter is derived based on the graph spectral transform and the estimated graph filter parameters. Then, the signal is processed using the graph filter to produce an output signal. The processing can enhance signals such as images by denoising or interpolating missing samples.

主权项

1. A method for processing an input signal represented as a graph, comprising:
employing a processor executing computer executable instructions stored on a computer readable memory to facilitate performing the steps of: acquiring the input signal, wherein the input signal is an image that is an unenhanced image including noise; acquiring a training data set, wherein the training data set includes pairs of training signals, wherein each pair of training signals includes an unenhanced training signal with noise and a corresponding enhanced training signal with reduced noise, and wherein the training signals are in a form of images; determining a graph spectral transform as an orthogonal set of eigenvectors based on the graph, wherein the graph includes vertices connected by edges having associated weights, and wherein the weights are based on a guidance signal in a form of a guidance texture image; estimating, in a graph spectral domain, parameters of a graph filter based on the training data set; deriving the graph filter based on the graph spectral transform and the graph filter parameters; and processing the input image using the graph filter to produce an output image, wherein the output image is an enhanced image with reduced noise that provides an increased understanding of a displayed image over an unenhanced displayed image with noise.