Improving the Performance of Single Chip Image Capture Devices

Single chip charge-coupled devices (CCDs) coupled with filters for isolating red, green, and blue color content are commonly used to capture color images. While this is more cost effective than multiple chip systems, best results are obtained when full RGB color information is obtained for every point in an image. The process of color subsampling in a single chip system degrades the resulting image data by introducing artifacts such as blurry edges and false coloring. We propose an algorithm for enhancing color image data that were captured with a typical single chip CCD array. The algorithm is based on stochastic regularization using a Markov random field model for the image data. This results in a constrained optimization problem, which is solved using an iterative constrained gradient descent computational algorithm. Results of the proposed algorithm show a marked improvement over the original sampled image data

Advances on CMOS image sensors

This paper offers an introduction to the technological advances of image sensors designed using complementary metal–oxide–semiconductor (CMOS) processes along the last decades. We review some of those technological advances and examine potential disruptive growth directions for CMOS image sensors and proposed ways to achieve them. Those advances include breakthroughs on image quality such as resolution, capture speed, light sensitivity and color detection and advances on the computational imaging. The current trend is to push the innovation efforts even further as the market requires higher resolution, higher speed, lower power consumption and, mainly, lower cost sensors. Although CMOS image sensors are currently used in several different applications from consumer to defense to medical diagnosis, product differentiation is becoming both a requirement and a difficult goal for any image sensor manufacturer. The unique properties of CMOS process allows the integration of several signal processing techniques and are driving the impressive advancement of the computational imaging. With this paper, we offer a very comprehensive review of methods, techniques, designs and fabrication of CMOS image sensors that have impacted or might will impact the images sensor applications and markets

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

Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

Holographic opto-fluidic microscopy.

Over the last decade microfluidics has created a versatile platform that has significantly advanced the ways in which micro-scale organisms and objects are controlled, processed and investigated, by improving the cost, compactness and throughput aspects of analysis. Microfluidics has also expanded into optics to create reconfigurable and flexible optical devices such as reconfigurable lenses, lasers, waveguides, switches, and on-chip microscopes. Here we present a new opto-fluidic microscopy modality, i.e., Holographic Opto-fluidic Microscopy (HOM), based on lensless holographic imaging. This imaging modality complements the miniaturization provided by microfluidics and would allow the integration of microscopy into existing on-chip microfluidic devices with various functionalities. Our imaging modality utilizes partially coherent in-line holography and pixel super-resolution to create high-resolution amplitude and phase images of the objects flowing within micro-fluidic channels, which we demonstrate by imaging C. elegans, Giardia lamblia, and Mulberry pollen. HOM does not involve complicated fabrication processes or precise alignment, nor does it require a highly uniform flow of objects within microfluidic channels

Multi-contrast imaging and digital refocusing on a mobile microscope with a domed LED array

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope--a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities

Study of optical techniques for the Ames unitary wind tunnel: Digital image processing, part 6

A survey of digital image processing techniques and processing systems for aerodynamic images has been conducted. These images covered many types of flows and were generated by many types of flow diagnostics. These include laser vapor screens, infrared cameras, laser holographic interferometry, Schlieren, and luminescent paints. Some general digital image processing systems, imaging networks, optical sensors, and image computing chips were briefly reviewed. Possible digital imaging network systems for the Ames Unitary Wind Tunnel were explored