Holography provides a means for indirect acquirement and reconstruction of 3-D object features. Here, we demonstrate high-resolution viewpoint object inference by formulating the object's reconstruction in the framework of compressive sensing. Further, when the object is dominated by speckle noise and cannot be considered to be sparse, we propose a digital resampling diversity compressive sensing approach to reconstruct a high-quality viewpoint inferred object. The results can be used in all types of holography for display and research purposes.

Abstract:In this paper, we present a new method of displaying Magnetic Resonance (MR) images taken from Multiple Sclerosis (MS) patients. We show that our method can potentially make the diagnostic process far more focused and concise. The method is implemented as an algorithm-based application, which automatically detects MS lesions and reduces the amount of reviewed images by 98% or more. In contrast to existing detection algorithms, our application utilizes five different types of MR images as well as the Digital Imaging and Communications in Medicine (DICOM) standard, supporting a wide range of data sets. After images are selected for file type and relevant brain region, each image is subjected to four separate algorithms, the results of which are combined into a single displayed image for the use of the diagnosing physician.

Tissues are characterized by a strong scattering of visible optical radiation, which prevents one from achieving deep-tissue imaging. We propose a computational imaging technique for the inference of specific macroscopic, spatial phase distribution features of the scattering media. The spatial phase distribution is reconstructed from several defocused intensity images. We empirically demonstrate the method by reconstructing the location of two fibula chicken bones, embedded within chicken breast tissue. The suggested technique is safe, using visible laser illumination, and noninvasive. It is also cost-effective since a simple optical system is used and the images are acquired using a conventional camera, and it does not require interferometric detection as well as direct access to the object in absence of the layer.