Ihrke, Ivo
Now showing 1 - 2 of 2
- Some of the metrics are blocked by yourconsent settings
Publication Access status: Metadata only , Optical system characterization in Fourier ptychographic microscopy(2024); ; Fourier ptychographic microscopy (FPM) is a recent technique to overcome the diffraction limit of a low numerical aperture (NA) objective lens by algorithmic post-processing of several low-resolution images. It can increase the space-bandwidth product of an optical system by computationally combining images captured under different illumination conditions. Vignetting determines the spatial extent of the bright and dark regions in the captured images. State-of-the-art analyses treat vignetting as a nuisance that needs to be reduced or excluded from algorithmic consideration using ad hoc decision rules. In contrast, this work investigates vignetting effects as a tool to infer a range of properties of the optical system. Generally, the goal of the FPM reconstruction algorithm is to achieve results that closely resemble the actual specimen at the highest resolution possible. However, as the optimization process does not necessarily guarantee a unique solution, we identify system properties that support alignment between computational predictions and empirical observations, potentially leading to a more accurate and reliable analysis. To achieve this, we characterize the individual system components of the experimental setup and compare experimental data to both, geometrical and wave optical simulations. We demonstrate that using vignetting as an analytical tool enables the modeling of the geometric and coherence properties of the optical system as evidenced by the good agreement between our simulation and experiment.Source Type:Article1 - Some of the metrics are blocked by yourconsent settings
Publication Access status: Metadata only , Performance Analysis of Optical Flow Techniques for Airborne SAR Image Registration<p>Image registration is a crucial step in interferometric synthetic aperature radar (InSAR) and in synthetic<br>aperture radar (SAR) tomography. Generally, a displacement of the sensors, e.g., due to different flight tracks, causes an image distortion that is dependent on the terrain height that is being observed. While ground truth digital elevation map (DEM) data are often available to roughly compensate for this distortion, there are application scenarios where the acquisition paths are too irregular or DEMs are not available. In such cases,<br>image registration via image processing is a suitable choice. While the SAR community prefers patch-based correlation techniques, the computer vision community has investigated the same issue from technically different points of view. In this Article, we study the performance of correlation- and computer visionbased image registration techniques for the image registration problem in SAR, in particular in airborne SAR without ground truth. We show that computer vision algorithms can outperform correlation-based techniques.</p>Source Type:Article1
