Adaptive foveated single-pixel imaging with dynamic super-sampling

As an alternative to conventional multi-pixel cameras, single-pixel cameras enable images to be recorded using a single detector that measures the correlations between the scene and a set of patterns. However, to fully sample a scene in this way requires at least the same number of correlation measurements as there are pixels in the reconstructed image. Therefore single-pixel imaging systems typically exhibit low frame-rates. To mitigate this, a range of compressive sensing techniques have been developed which rely on a priori knowledge of the scene to reconstruct images from an under-sampled set of measurements. In this work we take a different approach and adopt a strategy inspired by the foveated vision systems found in the animal kingdom - a framework that exploits the spatio-temporal redundancy present in many dynamic scenes. In our single-pixel imaging system a high-resolution foveal region follows motion within the scene, but unlike a simple zoom, every frame delivers new spatial information from across the entire field-of-view. Using this approach we demonstrate a four-fold reduction in the time taken to record the detail of rapidly evolving features, whilst simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This tiered super-sampling technique enables the reconstruction of video streams in which both the resolution and the effective exposure-time spatially vary and adapt dynamically in response to the evolution of the scene. The methods described here can complement existing compressive sensing approaches and may be applied to enhance a variety of computational imagers that rely on sequential correlation measurements.Comment: 13 pages, 5 figure

The High Energy Telescope on EXIST

The Energetic X-ray Imaging Survey Telescope (EXIST) is a proposed next generation multi-wavelength survey mission. The primary instrument is a High Energy telescope (HET) that conducts the deepest survey for Gamma-ray Bursts (GRBs), obscured-accreting and dormant Supermassive Black Holes and Transients of all varieties for immediate followup studies by the two secondary instruments: a Soft X-ray Imager (SXI) and an Optical/Infrared Telescope (IRT). EXIST will explore the early Universe using high redshift GRBs as cosmic probes and survey black holes on all scales. The HET is a coded aperture telescope employing a large array of imaging CZT detectors (4.5 m^2, 0.6 mm pixel) and a hybrid Tungsten mask. We review the current HET concept which follows an intensive design revision by the HET imaging working group and the recent engineering studies in the Instrument and Mission Design Lab at the Goddard Space Flight Center. The HET will locate GRBs and transients quickly (<10-30 sec) and accurately (< 20") for rapid (< 1-3 min) onboard followup soft X-ray and optical/IR (0.3-2.2 micron) imaging and spectroscopy. The broad energy band (5-600 keV) and the wide field of view (~90 deg x 70 deg at 10% coding fraction) are optimal for capturing GRBs, obscured AGNs and rare transients. The continuous scan of the entire sky every 3 hours will establish a finely-sampled long-term history of many X-ray sources, opening up new possibilities for variability studies.Comment: 10 pages, 6 figures, 3 tables, SPIE conference proceedings (UV, X-ray, and Gamma-Ray Space Instrumentation for Astronomy XVI, 7435-9

Disparity map generation based on trapezoidal camera architecture for multiview video

Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities, the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video remains a huge challenge. This paper presents the mathematical description of trapezoidal camera architecture and relationships which facilitate the determination of camera position for visual content acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera Architecture is that it allows for adaptive camera topology by which points within the scene, especially the occluded ones can be optically and geometrically viewed from several different viewpoints either on the edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate description could very well be used to address the issue of occlusion which continues to be a major problem in computer vision with regards to the generation of depth map

On evolution of CMOS image sensors

CMOS Image Sensors have become the principal technology in majority of digital cameras. They started replacing the film and Charge Coupled Devices in the last decade with the promise of lower cost, lower power requirement, higher integration and the potential of focal plane processing. However, the principal factor behind their success has been the ability to utilise the shrinkage in CMOS technology to make smaller pixels, and thereby have more resolution without increasing the cost. With the market of image sensors exploding courtesy their inte- gration with communication and computation devices, technology developers improved the CMOS processes to have better optical performance. Nevertheless, the promises of focal plane processing as well as on-chip integration have not been fulfilled. The market is still being pushed by the desire of having higher number of pixels and better image quality, however, differentiation is being difficult for any image sensor manufacturer. In the paper, we will explore potential disruptive growth directions for CMOS Image sensors and ways to achieve the same

Spectral imaging in preclinical research and clinical pathology.

Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings

Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions