Chandra Mouli

Bio: Chandra Mouli is an academic researcher from Micron Technology. The author has contributed to research in topics: Transistor & Field-effect transistor. The author has an hindex of 32, co-authored 216 publications receiving 3289 citations. Previous affiliations of Chandra Mouli include Aptina.

Method and apparatus for reducing effects of dark current and defective pixels in an imaging device

Abstract: A method and apparatus for identifying and compensating for the effects of defective pixels in high resolution digital cameras having image processing apparatus. The apparatus includes a storage system for storing data corresponding to either a dark current reference image and a white reference image and at least one actual image captured by a pixel array, and at least one processor coupled to the storage system for compensating the data corresponding to the actual image based upon the stored data. The method includes capturing and storing both dark and white reference images as well as capturing and storing actual images, identifying pixels that are affected by dark current or are defective pixels, reading data corresponding to pixels of an actual image affected by dark current or that are defective from the storage system and compensating the affected pixels.

Image sensor with improved surface depletion

Abstract: An image sensor device having a pixel cell with a pinned photodiode, which utilizes the fixed charge of an high K dielectric layer over the n-type region for the pinning effect without implanting a p-type layer over the n-type region, and methods of forming such a device.

Supression of dark current in a photosensor for imaging

Abstract: A pixel cell having a halogen-rich region localized between an oxide isolation region and a photosensor. The halogen-rich region prevents leakage from the isolation region into the photosensor, thereby suppressing dark current in imagers.

Metal mesh filter-comprising semiconductor image sensor

Abstract: A semiconductor image sensor utilizing a metal mesh filter to transmit light of a specific wavelength to a photoconversion device, and method of making said image sensor. Semiconductor image sensor pixel cells using varied metal mesh filters may be arranged in a Bayer pattern for color imaging. As a result, the need for using conventional polymer color filters in image sensor applications is eliminated.

Methods of forming field effect transistors and field effect transistor circuitry

Abstract: Methods of forming field effect transistors and resultant field effect transistor circuitry are described. In one embodiment, a semiconductive substrate includes a field effect transistor having a body. A first resistive element is received by the substrate and connected between the transistor's gate and the body. A second resistive element is received by the substrate and connected between the body and a reference voltage node. The first and second resistive elements form a voltage divider which is configured to selectively change threshold voltages of the field effect transistor with state changes in the gate voltage. In a preferred embodiment, first and second diode assemblies are positioned over the substrate and connected between the gate and body, and the body and a reference voltage node to provide the voltage divider.

Semiconductor device, and manufacturing method thereof

Abstract: An object is to provide a semiconductor device of which a manufacturing process is not complicated and by which cost can be suppressed, by forming a thin film transistor using an oxide semiconductor film typified by zinc oxide, and a manufacturing method thereof. For the semiconductor device, a gate electrode is formed over a substrate; a gate insulating film is formed covering the gate electrode; an oxide semiconductor film is formed over the gate insulating film; and a first conductive film and a second conductive film are formed over the oxide semiconductor film. The oxide semiconductor film has at least a crystallized region in a channel region.

Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data

Abstract: We present a simple and usable noise model for the raw-data of digital imaging sensors This signal-dependent noise model, which gives the pointwise standard-deviation of the noise as a function of the expectation of the pixel raw-data output, is composed of a Poissonian part, modeling the photon sensing, and Gaussian part, for the remaining stationary disturbances in the output data We further explicitly take into account the clipping of the data (over- and under-exposure), faithfully reproducing the nonlinear response of the sensor We propose an algorithm for the fully automatic estimation of the model parameters given a single noisy image Experiments with synthetic images and with real raw-data from various sensors prove the practical applicability of the method and the accuracy of the proposed model

Systems and methods for processing analyte sensor data

Abstract: Systems and methods for applying time-dependent algorithmic compensation functions to data output from a continuous analyte sensor. Some embodiments determine a time since sensor implantation and/or whether a newly initialized sensor has been used previously.

Cyclops: In Situ Image Sensing and Interpretation in Wireless Sensor Networks

Abstract: Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena. To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.

Cyclops: in situ image sensing and interpretation in wireless sensor networks

Abstract: Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena.To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.