Image sensors continuously develop in-field permanent hot pixel defects over time. Experimental measurements of
DSLR, point and shoot, and cell phone cameras, show that the rate of these defects depends on the technology (APS or
CCD) and on design parameters like imager area, pixel size, and gain (ISO). Increased image sensitivity (ISO) enhances
defects appearance and sometimes results in saturation. 40% of defects are partially stuck hot pixels, with an offset
independent of exposure time, and are particularly affected by ISO changes. Comparing different sensor sizes with
similar pixel sizes showed that defect rates scale linearly with sensor area, suggesting the metric of defects/year/sq mm.
Plotting this rate for different pixel sizes (7.5 down to 1.5 microns) shows that defect rates grow rapidly as pixel size
shrinks. Curve fitting shows an empirical power law with defect rates proportional to the pixel size to the power of -2.1
for CCD and to the power of -3.6 for CMOS. At 7um pixels, the CCD defect rate is ~2.5 greater than for CMOS, but
for 2.4um pixels the rates are equal. Extending our empirical formula to include ISO allows us to predict the expected
defect development rate for a wide set of sensor parameters.
Image sensors are continuously subject to the development of in-field permanent defects in the form of hot pixels.
Based on measurements of defect rates in 23 DSLRs, 4 point and shoot cameras, and 11 cell phone cameras, we show in
this paper that the rate of these defects depends on the technology (APS or CCD) and on design parameters the like of
imager area, pixel size, and gain (ISO). Increasing the image sensitivity (ISO) (from 400 up to 25,600 ISO range) causes
the defects to be more noticeable, with some going into saturation, and at the same time increases the defect rate.
Partially stuck hot pixels, which have an offset independent of exposure time, make up more than 40% of the defects
and are particularly affected by ISO changes. Comparing different sensor sizes has shown that if the pixel size is nearly
constant, the defect rate scales with sensor area. Plotting imager defect/year/sq mm with different pixel sizes (from 7.5
to 1.5 microns) and fitting the result shows that defect rates grow rapidly as pixel size shrinks, with an empirical power
law of the pixel size to the -2.5. These defect rate trends result in interesting tradeoffs in imager design.
Reliability of image sensors is limited by the continuous development of in-field defects. Laboratory calibration on 21
DSLRs has revealed hot pixels as the main defect type found in all tested cameras, with 78% of the identified defects
having a time-independent offset. The expanded ISO range that exists in new cameras enables natural light
photography. However, the gain applied to all pixels also enhances the appearance of defects. Analysis of defects at
varying ISO levels shows that compared to the number of defects at ISO 400, the number of defects at ISO 1600 is 2-3
times higher. Amplifying the defect parameters helps differentiate faults from noise, thus detecting larger defect sets
and causes some hot pixels to become saturated. The distribution of defect parameters at various ISO levels shows
that the gain applied to faults with moderate defect magnitude caused 2-10% of the defects to saturate at short exposure
times (0.03-0.5s). With our expanded defect collection, spatial analysis confirmed the uniform distribution of defects,
indicating a random defect source. In our extended study, the temporal growth of defects is analyzed using our defecttracing
algorithm. We introduce an improved defect model which incorporates the ISO gain, allowing the detection of
defects even in short exposure images at high ISO and thus providing a wider selection of historical images and more
accurate defect tracing. Larger area sensors show more hot pixels, while hot pixel rates strongly grow as the pixel size
decreases to 2.2 microns.
Photogate APS pixels use a MOS capacitor created potential well to capture photocarriers. However, optical
absorption of the poly-silicon gate reduces photon transmission. We investigate multi-fingered photogates with
openings in the gate to increase photon collection. 0.18 μm CMOS standard and multi-fingered photogates were
implemented where the enclosed detection area is divided by 1, 3 and 5 poly fingers. Preliminary response comparison
with standard photogates suggested the sensitivity of 1-finger pixels dropped ~22% implying open areas collected 62%
of the photocarriers. The sensitivity of 3 and 5 finger pixels increased ~33 - 49% over standard, with open area
collection ~170 - 290% more photocarriers due to fringing field created potential wells. These results indicated at least 66% of the incident light is absorbed by the poly-silicon gate. In spectral response multi-fingered pixels showed an increase in sensitivity in the red (631 nm) - yellow (587 nm) - green (571 nm) wavelengths but a relative decline in the blue (470 nm) possibly due to more absorption in the Silicon Nitride insulator layers. Some Silicon Nitride (SixNy) compositions have higher absorption coefficients in the Blue than poly-silicon and thus may dominate the absorption in these photogates structures. Extended analysis on the potential well formation in the multi-fingered photogates was perform using 2-D device simulation. Simulated multi-fingered photogates showed the strength of the fringing field increased as the open area spacing between poly-fingered decreases; with the 5-finger having a nearly uniform depleted region over the entire photogate area.
The lifetime of solid-state image sensors is limited by the appearance of defects, particularly hot-pixels, which we have
previously shown to develop continuously over the sensor lifetime. Analysis based on spatial distribution and temporal
growth of defects displayed no evidence of the defects being caused by material degradation. Instead, high radiation
appears to accelerate defect development in image sensors. It is important to detect these faulty pixels prior to the use of
image enhancement algorithms to avoid spreading the error to neighboring pixels. The date on which a defect has first
developed can be extracted from past images. Previously, an automatic defect detection algorithm using Bayesian
probability accumulation was introduced and tested. We performed extensive testing of this Bayes-based algorithm by
detecting defects in image datasets obtained from four cameras. Our results have indicated that the Bayes detection
scheme was able to identify all defects in these cameras with less than 3% difference from visual inspected result. In
this paper, we introduce an alternative technique, the Maximum Likelihood detection algorithm, and evaluate its
performance using Monte Carlo simulations based on three criterias: image exposure, defect parameters and pixel
estimation. Preliminary results show that the Maximum likelihood detection algorithm is able to achieve higher
accuracy than the Bayes detection algorithm, with 90% perfect detection in images captured at long exposures
Bimetallic thin-films of Bi/In act as negative thermal resists when laser exposure pulse (7mJ/sq. cm for 4 nsec)
converts the film into a transparent eutectic metallic oxide alloy. Resist transparency varies with exposed laser power,
changing from <0.1% (3.0 OD) unexposed to >60% (0.22 OD) exposed. This generates direct-write gray scale
photomasks, and adding a feedback system where the transparency is measured and adjusts the writing process to
account for local variations in the film, achieves >64 gray level control. These resists are also wavelength invariant,
operating from visible to EUV with a resolution >42nm after development using a diluted RCA-2 solution
(HCl:H<sub>2</sub>O<sub>2</sub>:H<sub>2</sub>0 @ 1:1:48) with a gamma of 2-18. Longer duration exposures with lower instantaneous intensities result
in lower gammas, while shorter exposures with higher energies give higher gammas. One limitation on these resists is
that the exposure energy must be delivered in a single pulse. This limitation puts pulse energy requirements into the mJ
per pulse range: greater than desired for EUV exposure systems. Bimetallic thermal resists remain almost unaffected
during a sub-threshold exposure that does not reach the activation energy. It has been shown that the resist and substrate
can be heated below the threshold energy, to temperatures of at least 90°C, without creating any exposure of the resist.
In this research, Bi/In resists are heated through a range of substrate temperatures, measured for their optical exposure
requirements and gammas under these conditions, and used to determine if substrate heating can improve the film's
The reliability of solid-state image sensors is limited by the development of defects, particularly hot-pixels, which we have previously shown develop continuously over the sensor lifetime. Our statistical analysis based on the distribution and development date of defects concluded that defects are not caused by single traumatic incident or material failure, but rather by an external process such as radiation. This paper describes an automated process for extracting defect temporal growth data, thereby enabling a very wide sample of cameras to be examined and studied. The algorithm utilizes Bayesian statistics to determine the presence and absence of defects by searching through sets of color photographs. Monte Carlo simulations on a set of images taken at 0.06 to 0.5sec exposures demontrating that our tracing algorithm is able to pinpoint the defect development date for all the identified hot pixels within ±2 images. Although a previous study has shown that in-field defects are isolated from each other, image processing functions applied by cameras such as the demosaicing algorithm were found to casue a single defective pixel to appear as a cluster in a color image, increasing the challenge pinpointing the exact location of hot defects.