Reconstruction Of Dynamic Objects Research Articles

Complete description of effects on reconstruction of dynamic objects from time-averaged digital holography to high-speed digital holography

Time-averaged holography (TAH) is a specialized technique for studying objects subjected to sinusoidal vibration, characterized by presenting a Bessel J0 envelope in the object’s reconstruction, a condition that occurs when the vibration period is much shorter than the hologram exposure time. In this work, we present an analytical expression that describes the reconstruction effects when both the exposure time and the period can take arbitrary values, allowing the application of the TAH technique for exposure times as fractions of the period. We observe that the presented function contains higher-order Bessel functions. Additionally, we found that the envelope not only depends on the relationship between the exposure time and the vibration period but is also directly related to the vibration amplitude. The expression we introduce applies to conditions where exposure times are very short, possible with pulsed lasers, called high-speed holography (HSH), where the object reconstructs as if it were static. This mathematical expression serves as a bridge that continuously connects the techniques of HSH and TAH, enabling a smooth transition between both techniques.

3-D Reconstruction of Dynamic Objects With Dual-Domain Modulation Strategy

3-D Reconstruction of Dynamic Objects With Dual-Domain Modulation Strategy

Reconstruction of dynamic objects with affine deformations in computerized tomography

Abstract. The data acquisition in computerized tomography takes a certain amount of time since the x-ray source has to be rotated around the specimen. An object that changes during the scanning causes inconsistent data sets. To avoid the motion artefacts in reconstructions, the algorithm has to take the dynamic behavior of the specimen into account. In this context, some a priori information about the movement is required. A reconstruction method is proposed that compensates for the motion with a special focus on affine deformations. It also permits the combination of reconstruction and image analysis tools to extract features of the object without motion artefacts. The algorithm is validated with a numerical example from medical imaging.