The optical-multiplex system is comprised of an image sensor, a multi-lens array and signal processing unit. The key
feature of the optical-multiplex system is that each pixel of the image sensor captures multiple data of the object through
multi-lenses and the object data is obtained by processing the raw data output from the optical-multiplex image sensor.
We are now able to report that our system can improve the signal-to-noise ratio of the image output from the opticalmultiplex
system by changing the shading characteristics of the multi-lenses in the optical-multiplex system. In a model
of the system for simulation purposes, an optical-multiplex system with five lenses is used. The five lenses are located at
the center, upper, lower, left and right above an image sensor. We calculate the signal-to-noise ratio of the image output
from the optical-multiplex system by changing the shading characteristics of the four lenses located at the upper, lower,
left and right. The best signal-to-noise ratio of this image output by the optical-multiplex system is 8.895 dB better than
that of a camera with a single lens. This value is beyond the previous report value of 3.764 dB.
We have previously reported an image capturing system called the optical-multiplex system comprised of an image
sensor and a multi-lens array, which is compact and light and has a deep depth of field. In the system, light passes
through five lenses in an aperture sheet and the object is detected by an image sensor. This system is unique because the
object data passing through each of the lenses is a specific range of data, which is coordinated on the pixel array. This is
in contrast to the current multi-lens systems, in which the object data from each lens is completely independent.
We are now able to report that our system can coordinate data from both an object at a very far distance and an object at
a measurable distance, suggesting that information from these two categories of objects can be separated by the opticalmultiplex
system using new algorithm.
I have developed for cameras a new system of capturing images called the "optical-multiplex" system. The system is
comprised of an image sensor and a multi-lens array (or an array of pin holes). This system has the advantages of being
compact and light and being able to provide a deep depth of field. In a model of the system for simulation purposes,
light passes through five pin holes in an "aperture sheet" and the resulting object information is detected by the image
sensor and processed by the signal-processing unit, which outputs the "optical-multiplex" signal. The simulation model
incorporating both signal and noise shows that most pixels in this new system have a better signal-to-noise ratio than in
the conventional single-lens system.
We found that accurate estimation of the actual resist patterns and impurity profiles is the key point in the case of image sensors below 2.5 um square cell size. We apply a resist patterning process model to our process/device simulation. In the photolithography process simulation, each patterned resist layer exhibits own resist corner rounding regarding as differences such as resist thickness and wavelength of stepper. For the ion implant processes and thermal processes, channeling and doped impurity diffusion models are newly applied. We introduced two dimensional Monte Carlo simulation in order to estimate channelings affected by impurity species, accelerating voltage of implanter and crystallographic orientation. This enables to get impurity profiles of implant processes with mega order accelerating energy. Three dimensional impurity diffusion profiles can be obtained by using the optimized ratio of lateral diffusion to perpendicular diffusion. We have confirmed the advantage of the new simulation method by evaluation of device characteristics in small size CCDs.