Modeling and optimizing through plenoptic function for the dual lenticular lens-based directional autostereoscopic display system.

We propose an autostereoscopic display system that ensures full resolution for multiple users by directional backlight and eye tracking technology. The steerable beam formed by directional backlight can be regarded as the result of sparsely sampling the light field in space. Therefore, we intuitively propose an optimization algorithm based on the characterization for the state of the steerable beams, which is computed in matrix form using the plenoptic function.

Wavelength-multiplexed stereoscopic LC display using scanning backlight.

A stereoscopic display system based on a wavelength-multiplexed and time-multiplexed technique is introduced. The system includes white LEDs, complementary multiband bandpass filters, 30 double-side-lit light guide bars, and a liquid crystal display panel, as well as a pair of complementary multiband bandpass filter glasses. The LEDs are divided into two groups, and each group is covered with a kind of complementary multiband bandpass filter.

Continuous wavelet transform and iterative decrement algorithm for the Lidar full-waveform echo decomposition.

In this paper, we propose a continuous wavelet transform and iterative decrement algorithm to decompose the light detection and ranging (LiDAR) full-waveform echoes into a series of components, each of which can be assumed as Gaussian essentially. We calculate the scale of continuous wavelet transform in real time according to the relationship between the center frequency of the mother wavelet and the approximate frequency of the transmitted laser pulse. The approximated frequency is calculated according to the half-width of the effective part of transmitted laser pulse.

Lidar full-waveform decomposition based on empirical mode decomposition and local-Levenberg-Marquard fitting.

The light detection and ranging (LIDAR) full-waveform echo decomposition method based on empirical mode decomposition (EMD) and the local-Levenberg-Marquard (LM) algorithm is proposed in this paper. The proposed method can decompose the full-waveform echo into a series of components, each of which can be assumed as essentially Gaussian. The original full-waveform echo is decomposed into the intrinsic mode functions (IMFs) and a final residual by using the EMD first.