Human visual system singularity map analyses

This paper has analyzed the day and night images using the novel concept called hard (day image) and soft (thermal diffusion night image) singularity maps (SM) that are biologically extracted by the lateral inhibition mechanism (LIM) of human visual system (HVS). The SM has provided us with a much less redundant data (from 2D-image pixels map (PM) to 1D boundary image map that has usually three orders of magnitude less data). Consequently, the correspondence exists uniquely among neighborhood frames in terms of the different slope values at image corners solving the optical flow problem for the video compression (Szu & Hsu, J. Elect. Imaging, V.7, No.4, pp.755-769, Oct. 1998). In this paper, some efficient computational methods: min-max picking, and next order Cellular Neural Network implementing the anti-diffusion Laplacian, can obtain the SM without the convolution broadening based on Sobel and Canny edge operators. However, the differentiation operation may produce a false singularity under noise, and thus we apply the Hermitian wavelets to obtain the noisy singularity (Szu et al. "Hermitian Hat Wavelet Design for Singularity Detection in Paraguay River Level Data Analyses," Proc. SPIE Wavelet Applications V.3078, pp.96-115, 1997).