Abstract
Nonlinear diffusion filters (NDF) are well-known in image processing and computer vision areas, particularly denoising, smoothing, segmentation, and restoration of images. In this paper we focus on a novel NDF application, namely denoising of single-trials of auditory brainstem responses (ABRs). By using NDF we show that from an original matrixform image of the single-trials, we are able to denoise the image using NDF, resulting in a better extraction of information such as morphology, and latency of the ABRs according to the intensity levels. This technique offers the advantage of rotation-invariance in comparison to other wellknown methods, e.g, wavelet denoising based on maximally decimated filter banks, due to an adaptive diffusion feature. It is concluded that NDF represents a novel and useful approach for the analysis of single-trials of ABRs.
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