An indirect time-of-flight (ToF) CMOS image sensor has been designed with 4-tap 7 μm global shutter pixel in back-side illumination process. 15000 e- of high full-well capacity (FWC) per a tap of 3.5 μm pitch and 3.6 e- of read-noise has been realized by employing true correlated double sampling (CDS) structure with storage gates (SGs). Noble characteristics such as 86 % of demodulation contrast (DC) at 100MHz operation, 37 % of higher quantum efficiency (QE) and lower parasitic light sensitivity (PLS) at 940 nm have been achieved. As a result, the proposed ToF sensor shows depth noise less than 0.3 % with 940 nm illuminator in even long distance.

This paper presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration trench capacitors (LOFITreCs) exhibiting over 120dB dynamic range with 11.4Me- full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70dB. The measured SNR at all switching points were over 35dB thanks to the proposed two-stage LOFITreCs.

In this paper we present planar microlenses designed to improve the sensitivity of SPAD pixels. We designed diffractive and metasurface planar microlens structures based on rigorous optical simulations. The current melted microlens solution and designed diffractive microlens were implemented on STMicroelectronics 40nm CMOS testchips (32 × 32 SPAD array), and average gains of 1.9 and 1.4 in sensitivity respectively were measured, compared to a SPAD without microlens.

Dynamic vision sensors are growing in popularity for Computer Vision and moving scenes: its output is a stream of events reflecting temporal lighting changes, instead of absolute values. One of its advantages is fast detection of events, which are asynchronously read as spikes. However, high event data throughput implies an increasing workload for the read-out. That can lead to data loss or to prohibitively large power consumption for constrained devices. This work presents a scheme to reduce data throughput by using near pixel pre-processing: less events codifying temporal change and intensity slope magnitude are generated. Our simulated example depicts a data throughput reduction down to 14 %, in the case of the most aggressive version of our approach.

We are using image systems simulation technology to design a digital camera for measuring fluorescent signals; a first application is oral cancer screening. We validate the simulations by creating a camera model that accurately predicts measured RGB values for any spectral radiance. Then we use the excitationemission spectra for different biological fluorophores to predict measurements of fluorescence of oral mucosal tissue under several different illuminations. The simulations and measurements are useful for (a) designing cameras that measure tissue fluorescence and (b) clarifying which fluorophores may be diagnostic in identifying precancerous tissue.

Proposed for the first time is a novel calibration empowered minimalistic multi-exposure image processing technique using measured sensor pixel voltage output and exposure time factor limits for robust camera linear dynamic range extension. The technique exploits the best linear response region of an overall nonlinear response image sensor to robustly recover via minimal count multi-exposure image fusion, the true and precise scaled High Dynamic Range (HDR) irradiance map. CMOS sensor-based experiments using a measured Low Dynamic Range (LDR) 44 dB linear region for the technique with a minimum of 2 multi-exposure images provides robust recovery of 78 dB HDR low contrast highly calibrated test targets.

Subsurface scattering gives a distinct look to many everyday objects. However, until now, systems to acquire subsurface scattering have assumed that the subsurface displacement and angle of scattering are completely independent of the angle of incident. While this independence substantially simplifies the acquisition and rendering of materials where it holds true, it makes the acquisition of other materials impossible. In this paper, we demonstrate a system that can quickly acquire the full anisotropic subsurface scattering at a given point. Unlike many existing commercial acquisition systems, our system can be assembled from off-the-shelf optical component and 3D printed/cut parts, making it accessible at a low price. We validate our device by measuring and fitting a dipole model for material exhibiting isotropic subsurface scattering as well as comparing real-world appearance with rendering of anisotropic material under incident laser beam illumination.

Experimentally demonstrated for the first time is Coded Access Optical Sensor (CAOS) camera empowered robust and true white light High Dynamic Range (HDR) scene low contrast target image recovery over the full linear dynamic range. The 90 dB linear HDR scene uses a 16 element custom designed test target with low contrast 6 dB step scaled irradiances. Such camera performance is highly sought after in catastrophic failure avoidance mission critical HDR scenarios with embedded low contrast targets.

The United States of America has an estimate of 84,000 dams of which approximately 15,500 are rated as high-risk as of 2016. Recurrent geological and structural health changes require dam assets to be subject to continuous structural monitoring, assessment and restoration. The objective of the developed system is targeted at evaluating the feasibility for standardization in remote, digital inspections of the outflow works of such assets to replace human visual inspections. This work proposes both a mobile inspection platform and an image processing pipeline to reconstruct 3D models of the outflow tunnel and gates of dams for structural defect identification. We begin by presenting the imaging system with consideration to lighting conditions and acquisition strategies. We then propose and formulate global optimization constraints that optimize system poses and geometric estimates of the environment. Following that, we present a RANSAC frame-work that fits geometric cylinder primitives for texture projection and geometric deviation, as well as an interactive annotation frame-work for 3D anomaly marking. Results of the system and processing are demonstrated at the Blue Mountain Dam, Arkansas and the F.E. Walter Dam, Pennsylvania.