The data of Anderson and Burr [1985. Vision Research, 25, 1147-1154] on the temporal-frequency (TF) specificity of noise maskers indicate that the effect of TF masking is broad and varies across spatial frequency (SF) channels. One subtle but significant feature of the data is that the TF at which the effect of masking is maximal falls continuously as the test TF falls. This continuous shift is...

We develop a new filter which combines spatially adaptive noise filtering in the wavelet domain and temporal filtering in the signal domain. For spatial filtering, we propose a new wavelet shrinkage method, which estimates how probable it is that a wavelet coefficient represents a “signal of interest” given its value, given the locally averaged coefficient magnitude and given the global subband...

Abstract: This paper proposes a network architecture to compute on-line the temporal crosscorrelation function between two signals, either stationary or locally stationary. We show that the weights of a multi-FIR (Finite Impulse Response) filter trained with a teacher forcing anti-Hebbian rule encode the crosscorrelation function between the input and the desired response. We extend this networ...

been used to compare the commonly used polynomial regression (PR) filter with more advanced adaptive filtering techniques for clutter removal. More specifically, three adaptive filtering techniques were used in the comparison. The mean-frequency (MF) filter adapts to the tissue movement by down-mixing the temporal signal with the mean Doppler frequency. The varying-frequency (VF) filter adapts ...

| We describe a general technique for specifying trajectories of controllable imaging parameters in an active vision system so that temporal integration processes are optimized. The technique assumes that a Kalman lter is used to perform the temporal integration of measurements and is based on determining, at each point in time, the set of imaging parameter values that minimizes the trace of th...

Abstract The discriminative correlation filter (DCF)-based tracking methods have achieved remarkable performance in visual tracking. However, the existing DCF paradigm still suffers from dilemmas such as boundary effect, degradation, and aberrance. To address these problems, we propose a spatio-temporal joint aberrance suppressed regularization (STAR) tracker under unified framework of response...

This paper presents a general approach for obtaining optimal filters as well as filter sequences. A filter is termed optimal when it minimizes a chosen distance measure with respect to an ideal filter. The method allows specification of the metric via simultaneous weighting functions in multiple domains, e.g. the spatio-temporal space and the Fourier space. It is shown how convolution kernels f...