<title>Design Considerations For A Solid-State Image Sensing System</title>

A software for simulation of CCD solid-state imagers has been designed. The software consist of simulators for imager process modeling, two and one dimensional charge and potential distribution modeling and simulators for modeling of main characteristics such as spectral response (SR), spectral sensitivity (SS), full noises (FN), and modulation transfer function (MTF). These characteristics may be so calculated jointly for optical blocks (lens system) and solid-state imager which may be based on charge-coupled devices, photodiodes, and photoresistors. Some methods and algorithms are examined for creating of photoelectric, SR, SS, FN and MTF simulators.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

An improved way of using the traditional Hartmann test has been evolved to measure spherical aberrations of photographic lenses. Instead of photographic plates, a solid-state linear image sensor was successfully used to achieve improvements in accuracy and in measuring efficiency. It was found possible to locate the intersection of a ray with the image plane in a few seconds, with an error of less than 0.3 microm. Two standard lenses of known data were measured to compare the results of the experiments and the calculations. The precision of the method is briefly discussed theoretically and experimentally.

One of the most dramatic demonstrations of the continuing advancement in VLSI has been the solid-state image sensor. Since the first array demonstration in 1967, the increase in pixel density in image sensors has matched the increase in cell density in dynamic memories. Today, image sensors with densities of 360,000 elements are available for consumer applications, and sensors with well over a million elements have been developed for government and scientific applications. Although electronic imaging has dominated the commercial and government market for many years, widespread application in consumer products has been limited by the high cost and low resolution of solid-state sensors as compared to vidicon-type tubes. Now, however, the cost of image sensors for television applications has fallen to a point at which it is attractive to design consumer products such as video cameras using solid-state image sensors. As a result, image sensors have entered the consumer marketplace as well. We discuss some of the advances made at Eastman Kodak Company in two areas: very high-speed image sensors and very high-density color image sensors. A brief introduction to image sensor architecture is presented, followed by descriptions of a 2000-frame/second sensor for high-frame-rate imaging and a 360,000-pixel color sensor for imaging photographic negatives.

Today, CCD and CMOS image sensors have found many applications in general public domains. However their use for scientific and space applications requires high electro optical performances and strong abilities to predict them prior to the image sensors design and conception. Sensitivity and image quality are two important electro-optical characteristics for an image sensor. The Quantum Efficiency (QE) and the Modulation Transfer Function (MTF) are respectively the common metrics used to quantify them. Because of an important number of parameters influencing the MTF and the QE, their analytical calculation is not an easy task. This paper describes an analytical model of MTF and QE of CCD and CMOS image sensors. The model has been developed in order to take into account a maximum number of parameters: pixel size, photosensitive area size and shape, EPI-layer and substrate doping concentration, junction depth. The effect of top layer oxide stacks on the resulting optical transmission coefficient and so on QE can also be taken into account. The study is established in the case of CMOS photodiode pixels and buried channel CCD pixels. The MTF and QE modeling results are compared with experimental results. MTF and QE measurements are realized on different pixels types having different photosensitive area shapes and using different technologies. A part of these measurements are performed on a frontside-illuminated CMOS sensor and on a thinned backside-illuminated CMOS image sensor, both of them are manufactured using CMOS technology dedicated to image sensors. The other part of MTF and QE measurements are performed on thinned backside-illuminated N-buried channel CCD sensor. Finally the MTF and QE models are used to make performance predictions, and the effects of various parameters on the MTF and the QE are discussed.

Classical models used to calculate the Modulation Transfer function (MTF) of a solid-state image sensor generally use a sinusoidal type of illumination. The approach, described in this paper, consists in considering a point-source illumination to built a theoretical three-dimensional model of the diffusion and the collection of photo-carriers created within the image sensor array. Fourier transform formalism is used for this type of illumination. Solutions allow to evaluate the spatial repartition of the charge density collected in the space charge region, i.e. to get the Pixel Response Function (PRF) formulation. PRF enables to calculate analytically both MTF and crosstalk at every needed wavelengths. The model can take into account a uniformly doped substrate and an epitaxial layer grown on a highly doped substrate. The built-in electric field induced by the EPI/Substrate doping gradient is also taken into account. For these configurations, MTF, charge collection efficiency and crosstalk proportion are calculated. The study is established in the case of photodiode pixel but it can be easily extended to pinned photodiode pixels and photogate pixels.

The pixel array of BSI CMOS image sensor is a kind of photoelectric device to obtain 2D image information. The image quality was evaluated by the modulation transfer function (MTF) of BSI CMOS image sensor pixel at Nyquist frequency. With the decreasing pixel size of BSI CMOS image sensor and the increasing spatial resolution, it is more and more difficult to improve the MTF at Nyquist frequency. According to the theoretical analysis, MTF is composed of aperture MTF and diffusion MTF, the comprehensive MTF function is usually obtained by the multiplication relationship between the two MTFs in the frequency domain. Aperture MTF and diffusion MTF have different influence factors and calculation functions, but they are related to the size of the opening. The opening here represents the sensitivity aperture and photo-sense region respectively. The smaller the opening of the detector pixel, the larger MTF will be. In this paper, the theoretical mechanism of MTF function is analyzed in detail, and the calculation results of MTF of BSI CMOS image sensor pixel under 8 typical optical wavelengths in 300nm-1000nm spectral band are listed.

The imaging payload of an EO satellite is required to obtain images of the Earth's surface underneath, as per required in terms of spatial and spectral resolution. In general terms, the essential performance criterion for an imaging system Is Its MTF (Modulation Transfer Function). The MTF can be calculated for certain components of IP like for Optics, Imaging sensor and IP electronics. Whereas there are other components as well, which do contribute towards MTF. These are relative motion of the object and IP, as well as different illumination angles of the illuminator (Sun) on the surface of earth, thus contributing the blur and blooming effect in IP, which again potentially affects the measurement of MIT for the IP. In order to simulate this environment on ground to calibrate the MTF of the IP or any camera that is prepared for the use on sin EO satellite, a flexible experimental setup has been devised and the results thereof have been presented, in this paper.

CMOS imagers based on Active Pixel Sensors (APS) are very important among others because of their possible technical innovations leading to ultra-low power image acquisition or efficient on-chip image preprocessing. Implementation of the image processing tasks (focal plane preprocessing and subsequent image processing) can be done effectively only with the consideration of known transfer characteristics of the imager itself. Geometrical Point Spread Function (PSF) depends on the certain geometric shape of active area in the particular design of CMOS APS. In this paper, the concept of Modulation Transfer Function (MTF) analysis is generalized to be applicable to the sampled structures of CMOS APS. Recalling theoretical results, we have analytically derived the detector MTF in the closed form for some special active area shapes. The paper also deals with the method based on pseudorandom image pattern with uniform power spectral density (PSD). This method allows to evaluate (in contrast to other methods) spatially invariant MTF including sampling MTF. It is generally known that a signal acquired by image sensor contains different types of noises. The superposition of these noises produces noise with a Gaussian distribution. The denoising method based on Bayesian estimator for implementation into the smart imager is presented.

In the process of designing a machine vision system, a critical step is selecting an image sensor and optics that satisfy required parameters of resolution. The resolution of the image sensor is determined by modulation transfer function (MTF). In this paper a method for the theoretical estimation of MTF based on topologic parameters of the image sensor and parameters of lenses is proposed. The purpose of this work is development a method that will be handy instrument for the resolution calculation of the imaging system on the initial stage of the designing process of the machine vision. In this paper dependency of MTF for different parameters of image sensor and lenses were presented. This method can be used for calculation resolution of imaging system in object’s plain domain. References 7, figures 3, tables1.

Despite advances in miniaturization of CMOS sensors, current submillimeter diameter microendoscopic systems rely on coherent fiber bundles to transfer the image from its collection point to the detector. Determining the resolution of an endoscopic optical system that employs a fiber bundle is nontrivial, and there is limited published information about how to calculate the theoretical modulation transfer function (MTF) of a system that may include a distal lens, fiber bundle, relay optics, and a camera sensor. While the fiber bundle is frequently considered the resolution-limiting element, greater information may be gained from computing the full system MTF. In this paper, we describe a resolution cascade method that calculates theoretical MTFs for common components, as well as for the entire microendoscopic system. These theoretical calculations compare favorably to experimentally gathered data for four different optical configurations. The software developed for these calculations is freely available to predict the MTF of other coherent fiber bundle-based systems. Brief instructions and necessary assumptions/conditions are described.

In this paper, the meaning and appropriateness of complementary metal-oxide-semiconductor image sensor (CIS) modulation transfer function (MTF) is reconsidered. Two-dimensional (2-D) submicrometer spot scanning results are presented for industrial CIS, 2-D-MTF, characterizing CIS performance and resolution abilities is extracted and compared with the ideal one-dimensional (1-D) MTF profile estimation calculated for all spatial frequencies. "Inter" and "intra" pixel MTFs emphasizing pixel structure dependencies are defined. The domain of applicability of traditional 1-D sensor characterization methods is shown to be ambiguous and insufficient for modern anisotropic CIS designs, resembling the inability to account for the sensor internal structural effects. Furthermore, it was shown that 2-D characterization provides reliable information and enables better understanding and the most accurate description of device performance. In addition, the advantages (over the commonly referred 1-D-MTF) and necessities of 2-D-MTF are verified experimentally and clearly demonstrated in this paper

Due to their low-cost fabrication process and high efficiency, silicon-based Complementary Metal Oxide Semiconductor (CMOS) image sensors are the reference in term of detection in the visible range. However, their optical performances are toughly degraded in the Near Infrared (NIR). For such wavelengths, Silicon has a small absorption coefficient, leading to a very poor Quantum Efficiency (QE). A solution to improve it is to implement structures like pyramids that are etched in the Silicon layer. This will lead to diffraction inside the photodiode, enhancing the light path and therefore the absorption. Using Finite Difference Time Domain (FDTD) simulations, we demonstrated a huge QE enhancement at 940nm on real pixels, by implementing this kind of diffractive structures and we finally confirmed these results by characterizations. We obtained QE values up to 47% at 940nm for our 3.2μm pixel, corresponding to a gain of 2 comparing to a pixel without any diffractive structures. We also measured the Modulation Transfer Function (MTF), to evaluate how this figure of merit is impacted by the addition of these structures. As expected, the MTF was degraded when we added these diffractive patterns but were still high looking at the values. We indeed demonstrated MTF values going up to 0.55 at Nyquist/2 frequency and 0.35 at Nyquist frequency. Looking not only at QE values but also at MTF ones, these are very promising results that could be used in many different NIR applications like face recognition, Light Detection and Ranging (LIDAR) or AR/VR.

In this paper we critique the first order quantum efficiency and modulation transfer function (MTF) analysis for photocollection in both a finite and semi-infinite slab of semiconducting material. We derive the correct equations from first principles and perform a case study comparing photodetection in silicon and GaAs. This is of interest in the first order design of GaAs and silicon optical smart sensors and solid-state imagers.

We report a midinfrared dual-field-of-view (FOV) optical system design for an airborne electro-optical targeting system. To achieve miniaturization and weight reduction of the system, it has a common aperture and fore-optics for three different spectral wavelength bands: an electro-optic (EO) band (0.6~0.9 μm), a midinfrared (IR) band (3.6~4.9 μm), and a designation laser wavelength (1.064 μm). It is free to steer the line of sight by rotating the pitch and roll axes. Our design co-aligns the roll axis, and the line of sight therefore has a fixed entrance pupil position for all optical paths, unlike previously reported dual-FOV designs, which dispenses with image coregistration that is otherwise required. The fore-optics is essentially an achromatized, collimated beam reducer for all bands. Following the fore-optics, the bands are split into the dual-FOV IR path and the EO/laser path by a beam splitter. The subsequent dual-FOV IR path design consists of a zoom lens group and a relay lens group. The IR path with the fore-optics provides two stepwise FOVs (1.50° × 1.20° to 5.40° × 4.32°), due to the insertion of two Si lenses into the zoom lens group. The IR optical system is designed in such a way that the location and f-number (f/5.3) of the cold stop internally provided by the IR detector are maintained when changing the zoom. The design also satisfies several important performance requirements, including an on-axis modulation transfer function (MTF) that exceeds 10% at the Nyquist frequency of the IR detector pitch, with distortion of less than 2%.

Optical design of reflecting omnidirectional zoom optical system with peripheral half-field of view from 110° to 72° for day and night surveillance