Yinan Cao

Three-dimensional range-gated flash LIDAR for land surface remote sensing

Three-dimensional range-gated imaging is a new 3D sensing technique with higher resolution than 3D flash LIDAR, and has great potential in realizing high-resolution real-time 3D imaging to satisfy land surface remote sensing applications. In this paper, three existing approaches of realizing 3D range-gated LIDAR are introduced including their advantages and disadvantages. Among them, the two methods of gain modulation and range-intensity correlation can reconstruct a 3D scene from two gate images, which enable 3D flash imaging. We propose a 3D superresolution range-gated flash LIDAR based on triangular algorithm of range-intensity correlation, and further present a coding method based on triangular algorithm for high depth-to-resolution ratio. Some prototyping experiments and simulations are demonstrated.

Real-time remote three-dimensional superresolution range-gated imaging based on inter-frame correlation

High-resolution real-time three-dimensional imaging is important in 3D video surveillance, robot vision, and automatic navigation. In this paper, a three-dimensional superresolution range-gated imaging based on inter-frame correlation is proposed to realize high-resolution real-time 3D imaging. In this method, a CCD/CMOS with a gated image intensifier is used as image sensor, and depth information collapsed in 2D images is reconstructed by spatial-temporal inter-frame correlation with a resolution of about 1000×1000 full-frame pixels within a frame. Furthermore, under inter-frame correlation a 3D point cloud frame is generated at video rates corresponding to CCD/CMOS utilized. Finally, some proof simulation experiments are demonstrated.

Long range Gait recognition in range-gated viewing video by moment based descriptors

In complicated environment of low visibility, long range Gait receives increasing attention as a biometric in surveillance. Given the requirement to process sequences obtained by range-gated imaging system, computational demands are high, motivating the development of basic approaches. Based on these baseline approaches, we use a family of moment descriptors to describe a single shape by using a masking circle, and analyze gait with specificity and speed using moments to acquire invariant properties. Results show that the Hu1 moment performs consistently better than other moments at discriminating between subjects. And by constraining the database to specific starting foot and direction of walk we are able to dramatically increase the recognition rate over 80%.

Automatic fishing net detection and recognition based on optical gated viewing for underwater obstacle avoidance

An automatic fishing net detection and recognition method for underwater obstacle avoidance is proposed. In the method, optical gated viewing technology is utilized to obtain high-resolution fishing net images and extend detection distance by suppressing water backscattering and background noise. The fishing net recognition is based on the proposed histograms of slope lines (HSLs) descriptors plus a support vector machine classifier. The extraction of HSL descriptors includes five steps of contrast-limited adaptive histogram equalization, the Gaussian low-pass filtering, the Canny detection, the Hough transform, and weighted vote. In the proof experiments, the detection distance of the fishing net reaches 5.7 attenuation length and the recognition accuracy reaches 93.79%.

Spatial difference shaping to improve range resolution in 3D super resolution range gated imaging

Three-dimensional super-resolution range-gated imaging has been developed for high-resolution 3D remote sensing with two range-intensity correlation algorithms under specific shapes of range-intensity profiles (RIP). However, pulsed lasers have a minimum pulse width which limits range resolution improvement. Here a spatial difference shaping method is proposed to break the resolution limitation. This method establishes a shaping filter, and the pre-reshaping gate images are reshaped by spatial difference and yield new gate images with the laser pulse width equivalently narrowed as half value which improves the range resolution. Furthermore, the boundary blurring caused by non-rectangular laser pulses are also eliminated.

A DSP-based video processing system for infrared small targets detection

A DSP based system is proposed to detect infrared small targets in thermal imaging. The core of the system is TMS320DM6467T, in which an ARM9 and a C64+ DSP are integrated. The system includes a video capture module, a video process module and a video output module. To detect small targets in the video, an algorithm based on maximum between-class variance method in wavelet domain is proposed. Video stream data is obtained by a thermal imager, and then processed in proposed system. Experiment shows that the system is capable of target detection for thermal imaging.

Target azimuth estimation for automatic tracking in range-gated imaging

Target tracking is of great importance in imaging system, which can be applied in surveillance, as well as salvage and rescue where 3D spatial coordinates are used to locate the target. Range-gated imaging system is capable of acquiring range information of targets. However, azimuth is also necessary to provide the spatial coordinates to achieve target tracking. This paper presents a target azimuth estimation method for range-gated imaging system, aiming at obtaining essential information for vision-based automatic tracking. Due to the noise and low contrast of range-gated image, median filter and histogram equalization are used. Then the Otsu method is performed to make the segmentation of target and background. After segmentation, morphologic transformation methods will be taken in order to delete false targets. With pixels of target extracted from the image, the centoid will be derived. Next the pinhole camera model is applied to work out the azimuth coordinate. Since the focus length of camera is needed in the formula, an NC (Numerical Control) zoom module is developed. In this module, a sliding potentiometer is connected to the focus motor in camera, which serves as a feedback of the focus. To read the focus length and control the focus motor, an MCU (with AD converter) is used. Once the target azimuth information is obtained, the pan-tilt control unit can track the target bit by bit automatically.

Target contour extraction for shipborne active range-gated imaging

Target acquisition is of great importance for ship borne range-gated night vision system which can achieve target finding, target tracing and ranging. A digital image processing algorithm is developed for the mentioned night vision equipment above. Target contour is extracted using Canny edge detection algorithm based on self-adapted Otsu threshold segmentation. Furthermore, edge thinning, edge connection and morphologic methods are implemented to ameliorate the acquired contour. Pixels inside the contour are collected utilizing horizontal-vertical traverse. After ship targets from range-gated equipment being all tested, target contour and inner pixels can both be acquired through this algorithm.