Surface Detection Using Local Energy for 3d Confocal Microscope Images

The ability to detect surfaces within confocal microscope images is important for the interpretation of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to detect some feature types that are important in confocal microscopy. The local energy feature detector developed by Morrone and Owens marks locations where there is congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature types: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented, quadrature pairs of 3D lters. To increase the speed of the convolution, the lters are designed in frequency space and multiplied by the image's Fourier transform. Some preliminary results are presented.