A novel (to the best of our knowledge), fast method to measure in-plane object motion in 1D with sub-pixel accuracy which complements the correlation technique is proposed. The method is verified experimentally using both visible and terahertz images. The absolute sum of grey level accumulated change is used to quantify object motion. The method requires calibration for each target, but only addition and subtraction operations. This results in a decrease of two orders of magnitude in the computation time.

Unlike coherent imaging techniques, light field imaging uses incoherent (white light) illumination to generate a digital hologram of three-dimensional (3D) objects in real time. Multiple projections (or elemental images) of a 3D object are captured using a microlens array attached to a digital camera. Orthographic projection images (OPIs) can be synthesized from the recorded elemental images. The synthesized intensity-based OPIs are then multiplied by the corresponding phase functions and combined to form a digital hologram (also known as an integral hologram) of a 3D object under illumination. In this study, we analyze the performance of a synthesized integral hologram under low light imaging (photon-counting) conditions. The feasibility of this technique is verified experimentally by capturing the elemental images and subsequently generating orthographic projection images and by varying photon counts to reconstruct the digital holograms.

A novel continuous-wave terahertz holography imaging system based on heterodyne detection is presented. It employs a field-effect transistor as a fast coherent detector for digital data recording.

Many applications in physics and engineering require non-invasive, precise object tracking, which can be achieved with image processing methods at very good cost-efficiency ratios. The traditional method for measuring displacement with subpixel resolution involves cross-correlation between images and interpolation of the correlation peak. While this method enables target tracking with a resolution of thousandths of a pixel, it is computationally intensive and susceptible to peak-locking errors. Recently, a new method based on discrete subtraction between images has been presented as an alternative to cross-correlation to improve computational efficiency, which also results in being free of peak-locking errors. This manuscript presents an experimental evaluation of the performance of the discrete subtraction method (DSM) and compares it with the cross-correlation method in terms of subpixel accuracy and deviation errors. Four different targets were used with apparent displacements as small as 0.002 px, which approaches the theoretical digital resolution limit. The results show that the discrete subtraction method is more sensitive to noise but does not suffer from peak-locking error, thus being a reliable alternative to the correlation method, mainly for calibration processes.

Fast and simple methods for motion estimation with subpixel accuracy are of interest in a variety of applications. In this paper, we extend a recently proposed method for quantifying 1D displacements with subpixel accuracy, referred to as the subtraction method (SM) to 2D motion. Simulation and experimental results are presented. The results indicate that any general motion in 2D involving combinations of in-plane motions in x and y can be determined using SM after a 1D calibration. The errors between the actual motion and estimated are examined.

Estimation of the delay between two signals has physical significance in synchronisation problems in, e.g. telecommunications, measurement of motion and vibration, and image registration. Low complexity algorithms can be performed extremely quickly even on limited hardware, and have improved energy consumption over more complex algorithms. We present a partial Fourier analysis of a previously reported algorithm to estimate the magnitude of the delay; the algorithm is the sum of absolute differences. The analysis offers insight into why the algorithm requires the absolute value operation. The algorithm is insensitive to direction of the delay, but the same analysis demonstrates that new approaches are possible to find the signed magnitude of the delay. Arising from that analysis, we propose one such algorithm, and demonstrate its efficacy in simulation, along with its robustness to additive and quantization noise. Our algorithm could be useful in a very wide range of applications, including image stitching, measurement of vibrations in buildings, and synchronisation problems in telecommunications.