Determining the limiting conditions of sampling interval and sampling angle for laser reflective tomography imaging in sensing targets with typical shapes

Hybrid regularization method for LRT image reconstruction under incomplete projections

“…Inverse Radon transform [10], filtered back projection (FBP) [11][12] and algebraic reconstruction technique (ART) [13][14][15] are common reconstruction algorithms in LRT. However, in actual detection, the collected echo data of LRT is usually missing or incomplete in angle owing to the complex and difficult detection conditions [16][17], which greatly reduces the effect of these traditional projection methods. As to this problem, Malik et al used the logical rules of a fuzzy inference system to compensate for missing data [18].…”

Reflective Tomography Lidar Image Reconstruction for Long Distance Non-Cooperative Target

“…The transmitting part is composed of a microchip laser, two reflectors, one beam splitter, and one expander system whereas the receiving part is composed of a receiving telescope and a 7.5 GHz avalanche photodiode (APD) detection module, along with a 15 GHz bandwidth Pin light detection module on the other side of the splitter. A laser pulse high-speed data acquisition module with a bandwidth of 4.25 GHz and a sampling rate of 50 GSPS is employed in the data acquisition part and the data processing part is controlled by the industrial personal computer and is able to complete real-time data processing [6]. The detailed schematic diagram of the LRT experimental system is shown in Figure 3.…”

“…Jin conducted reflection tomography lidar imaging by pulse detection to obtain the image of the conical object in the laboratory environment and experiment preliminarily on the LRT imaging with the incomplete view of the projection data [3][4][5]. Zhang determined the limiting conditions of the sampling interval and sampling angle for laser reflective tomography imaging in sensing targets with typical shapes [6,7]. Hu applied LRT to plane target centroid detection for the first time and proposed a method for calculating centroid distance using multi-angle echo data [8].…”

Hybrid regularization method for LRT image reconstruction under incomplete projections

“…Projection transformation methods including inverse Radon transform [10] and filtered back projection (FBP) [11][12] are commonly used reconstruction algorithms in LRT. However, in actual detection, the collected echo data of LRT is usually missing or incomplete in angle owing to the complex and difficult detection conditions [13][14], which greatly reduces the effect of these traditional projection methods. Related study on missing or incomplete data reconstruction can be found in some other areas like computed tomography (CT) reconstruction.…”