WeiHsuChaoTsunHanHuang: Difference between revisions
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== Introduction == | == Introduction == | ||
Sensor noise analysis is one of the most important features that we need to take care of when we are testing our sensors. Today, the CMOS image sensor is widely used by many smart phones. There are some common camera (sensor) noise that exist in such type of image sensor. One is fixed pattern noise (FPN) and the other one is temporal noise. For the former one, there are two major noise we have to further explore. One is PRNU and the other one is DSNU | Sensor noise analysis is one of the most important features that we need to take care of when we are testing our sensors. Today, the CMOS image sensor is widely used by many smart phones. There are some common camera (sensor) noise that exist in such type of image sensor. One is fixed pattern noise (FPN) and the other one is temporal noise. For the former one, there are two major noise we have to further explore. One is PRNU (Photo-Response Non-Uniformity) and the other one is DSNU (Dark Signal Non-Uniformity). For the temporal noise, read noise and dark noise are the two we are going to measure in this project. This project is going to give a high-level view of how to calculate and measure these values with different color channels and ISO speed. We aim to find some relationship or pattern during this project. | ||
== Background == | == Background == |
Revision as of 04:05, 19 November 2020
Introduction
Sensor noise analysis is one of the most important features that we need to take care of when we are testing our sensors. Today, the CMOS image sensor is widely used by many smart phones. There are some common camera (sensor) noise that exist in such type of image sensor. One is fixed pattern noise (FPN) and the other one is temporal noise. For the former one, there are two major noise we have to further explore. One is PRNU (Photo-Response Non-Uniformity) and the other one is DSNU (Dark Signal Non-Uniformity). For the temporal noise, read noise and dark noise are the two we are going to measure in this project. This project is going to give a high-level view of how to calculate and measure these values with different color channels and ISO speed. We aim to find some relationship or pattern during this project.
Background
Methods
Results
Conclusions
Appendix
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