Silicon Wafer Defect Self-Characterization with CCD Image Sensors

2005 ◽  
Vol 864 ◽  
Author(s):  
William C. McColgin ◽  
Alexa M. Perryy ◽  
Dean J. Seidler ◽  
James P. Lavine
Keyword(s):  
Image Quality ◽  
Silicon Wafer ◽  
Dark Current ◽  
Image Sensors ◽  
High Image Quality ◽  
Ccd Image ◽  
Silicon Defects ◽  
Very High

AbstractToday's CCD image sensors can provide very high image quality. However, used as a tool, they can also provide a sensitive window into defects in silicon, either intrinsic to the starting wafers or introduced during fabrication. In this paper, we examine some cases of known silicon defects and show how they can appear in, and be studied by, CCD imagers. As examples, we discuss epi-layer defects, slip defects, and dark-current rings.

Radiation-Induced Deep-Level Traps in CCD Image Sensors

2007 ◽  
Vol 994 ◽  
Author(s):  
Cristian Tivarus ◽  
William C. McColgin
Keyword(s):  
Dark Current ◽  
Deep Level ◽  
Image Sensors ◽  
Charge Coupled Devices ◽  
Radiation Induced ◽  
Ccd Image ◽  
Silicon Defects

AbstractDark current spectroscopy (DCS) is used to study deep level traps corresponding to the bright pixels that form the histogram “tails” of irradiated charge-coupled devices (CCD). We found four distinct traps, among which the double vacancy (V2) and the vacancy-phosphorous (VP) have the highest concentrations and generation rates. We show that DCS can be used to examine the annealing mechanisms of silicon defects to concentrations as low as 5 × 107 cm−3.

Dark Current Spectroscopy of Irradiated CCD Image Sensors

2008 ◽  
Vol 55 (3) ◽  
pp. 1719-1724 ◽  
Author(s):  
C. Tivarus ◽  
W. C. McColgin
Keyword(s):  
Dark Current ◽  
Image Sensors ◽  
Ccd Image

Probing Metal Defects in CCD Image Sensors

1995 ◽  
Vol 378 ◽  
Author(s):  
William C. McColgin ◽  
J. P. Lavine ◽  
C. V. Stancampiano
Keyword(s):  
Cross Sections ◽  
Dark Current ◽  
Deep Level ◽  
Energy Levels ◽  
Image Sensors ◽  
Current Generation ◽  
Charge Coupled Device ◽  
Iron Nickel ◽  
Relationship Of ◽  
Ccd Image

AbstractWe have investigated the role of heavy metals in causing visible pixel defects in Charge Coupled Device (CCD) image sensors. Using a technique we call dark current spectroscopy, we can probe for deep-level traps in the active areas of completed image sensors with a sensitivity of 1 × 109 traps/cm3 or better. Analysis of histograms of dark current images from these sensors shows that the presence of traps causes quantization in the dark current. Different metal traps have characteristic dark current generation rates that can identify the contaminant trap. By examining the temperature dependence of the dark current generation, we have calculated the energy levels and generation cross sections for gold, iron, nickel, and cobalt. Our results show the relationship of these traps to the “white spot” defects reported for image sensors.

Deep-Level Traps in CCD Image Sensors

1998 ◽  
Vol 510 ◽  
Author(s):  
William C. Mccolgin ◽  
James P. Lavine ◽  
Charles V. Stancampiano ◽  
Jeffrey B. Russell
Keyword(s):  
Dark Current ◽  
Deep Level ◽  
Image Sensors ◽  
Charge Coupled Device ◽  
Ccd Image

AbstractWe have extended by five the number of deep-level traps known to create dark current in charge-coupled device (CCD) image sensors. These include Mn, Pt, and three much weaker traps that are as yet unidentified. Using dark current spectroscopy (DCS) we show that the generation rates at 55°C range from 6400 electrons/s for Mn to only 2 electrons/s for the weakest trap, which lies 0.27 eV off mid-gap. These weak traps determine the bandwidths and resolution of the trap peaks seen in the dark current spectra.

High image quality QD image sensors for the SWIR range

2020 ◽  
Author(s):  
Pawel Malinowski ◽  
David Cheyns ◽  
Vladimir Pejovic ◽  
Luis Moreno Hagelsieb ◽  
Griet Uytterhoeven ◽  
...  
Keyword(s):  
Image Quality ◽  
Image Sensors ◽  
High Image Quality

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Improving a DWT-based compression algorithm for high image-quality requirement of satellite images

2011 ◽  
Author(s):  
Carole Thiebaut ◽  
Christophe Latry ◽  
Roberto Camarero ◽  
Grégory Cazanave
Keyword(s):  
Image Quality ◽  
Satellite Images ◽  
Compression Algorithm ◽  
Quality Requirement ◽  
High Image Quality
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