Low-power laser image enhancement via deep feature recovery for HDR 3D measurement.

Laser 3D measurement has gained widespread applications in industrial metrology . Still, it is usually limited by surfaces with high dynamic range (HDR) or the colorful surface texture of measured surfaces, such as metal and black industrial parts. Currently, conventional methods generally work with relatively strong-power laser intensities, which could potentially damage the sample or induce eye-safety concerns.

High dynamic range 3D measurement based on polarization and multispectrum co-modulation.

Three-dimensional (3D) shape measurement serves an important role in many areas, and fringe projection profilometry (FPP) is a widely used 3D measurement technique due to its non-physical contact and high speed. The real measurement scenarios are often mixtures of specular and diffuse reflections, causing overexposed and underexposed areas to co-exist. Currently, utilizing FPP to simultaneously measure overexposed and underexposed areas remains a challenge.

A master-slave surveillance system to acquire panoramic and multiscale videos.

This paper describes a master-slave visual surveillance system that uses stationary-dynamic camera assemblies to achieve wide field of view and selective focus of interest. In this system, the fish-eye panoramic camera is capable of monitoring a large area, and the PTZ dome camera has high mobility and zoom ability. In order to achieve the precise interaction, preprocessing spatial calibration between these two cameras is required.

Video denoising based on a spatiotemporal Kalman-bilateral mixture model.

We propose a video denoising method based on a spatiotemporal Kalman-bilateral mixture model to reduce the noise in video sequences that are captured with low light. To take full advantage of the strong spatiotemporal correlations of neighboring frames, motion estimation is first performed on video frames consisting of previously denoised frames and the current noisy frame by using block-matching method. Then, current noisy frame is processed in temporal domain and spatial domain by using Kalman filter and bilateral filter, respectively.