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Extreme High full well capacity camera to increase the sensitivity in interferometric microscopy – interview with MIT

Posted by Gretchen Alper on Thu, Jul 21, 2016

Adimec interviews Poorya Hosseini of MIT to discuss the use of extreme high full well capacity camera in interferometric microscopy

Optics Letters recently published a paper titled “Pushing phase and amplitude sensitivity limits in interferometric microscopy”.  For this research, the Adimec high full well (HFW) Q-2HFW-CXP camera was used.  The new 2 Megapixel CoaXPress camera (Q-2HFW-CXP) brings a 1440x1440 resolution at up to 550 fps based on 12 micron pixels. The design of the pixels in this global shutter CMOS image sensor, CMOSIS CSI2100, is optimized for maximum full well performance. The full well capacity (FWC) of over 2 million electrons per pixel is quite unique that is around 100 times higher compared to commonly available high speed CMOS sensor technology today (reference: 20 kel full well). This million-level electrons full well capacity per pixel results in extremely good shot noise performance of up to 63 dB SNR, making it possible to accurately detect very weak contrast variations in bright environments. The camera was developed as part of the FP7 funded CAReIOCA consortium.

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Topics: Applications

Advances in healthcare with extreme high full well capacity imaging innovations

Posted by Gretchen Alper on Wed, Jul 13, 2016

Adimec's Q-2HFW-CXP high full well capacity CMOS camera is enabling advances in cancer assesment

As part of the FP7 funded CAReIOCA consortium, Adimec has been involved in the development of an extreme full well, high speed camera for non-invasive optical imaging for cancer assessment. 

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Topics: Applications

How the 24h of Le Mans profits from low light CMOS cameras

Posted by Benny Koene on Thu, Jun 30, 2016

In the weekend of 18th and 19th of June, Porsche won the 24 Hours of Le Mans after Toyota got into problems in the final seven minutes. This year, for the first time, Adimec’s rugged security cameras with highly sensitive CMOS Global Shutter technology where used to broadcast the driver’s view on the road. The extreme environment inside the sports car with constantly changing levels of shock and vibration, changing temperatures and the requirement to have broadcast quality images during daytime and at night with low light make it a challenging environment for a camera.

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Topics: Applications

Get better image information from machine vision cameras – removing artifacts with flat field correction

Posted by Gretchen Alper on Thu, Jun 23, 2016

Flat Field Correction in Machine Vision Cameras

We recently published a series of articles about using Flat Field Correction in high-resolution Machine Vision cameras. 

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Topics: Image Quality Improvements

How to use Flat Field Correction in practice?

Posted by Benny Koene on Thu, Jun 16, 2016

Flat Field Correction (FFC) in cameras for Machine Vision Part 3

As we have discussed in previous articles, elsewhere on our blog, various types of flat field correction (FFC) exist. Depending on the variant, a flat field correction corrects for dark signal non-uniformities (DSNU), photo response non-uniformities (PRNU) and/or artifacts caused by the illumination and illumination optics. In this blog post we will briefly explain the required steps to make flat field correction work in practice.

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Topics: Image Quality Improvements

Which types of flat field corrections exist and why it matters for high resolution cameras?

Posted by Benny Koene on Thu, Jun 9, 2016

Flat Field Correction (FFC) in cameras for Machine Vision Part 2

Flat field correction is a widely used term as a lot of industrial and machine vision cameras have some form of correction algorithms to overcome image artifacts. However not all forms of flat field correction are the same and with the growing amount of pixels on a sensor, the variations in methods of how a flat field is achieved has only increased. In this article we will clarify the existing correction mechanisms.

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Topics: Image Quality Improvements

How to remove light source and illumination optics artifacts from your camera image

Posted by Benny Koene on Mon, Jun 6, 2016

Flat Field Correction (FFC) in cameras for Machine Vision Part 1

This is the first in a series of articles about using Flat Field Correction in high-resolution Machine Vision cameras.

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Topics: Image Quality Improvements

Moving from CCD to CMOS daylight cameras in global security systems

Posted by Gretchen Alper on Wed, May 25, 2016

There is a move from CCD to CMOS daylight cameras in global security systems with the increase in low light performance (better NIR sensitivity and lower noise) of the latest CMOS global shutter image sensors. Here are several articles that offer some tips on how to take advantage of the latest technology:

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Topics: Sensor Technology

How to interpret the Dynamic Range and Signal to Noise Ratio (SNR) in image sensor and industrial camera specifications

Posted by Gretchen Alper on Wed, May 18, 2016

With machine vision applications, some of the most important specifications beyond resolution and frame speed to determine whether the camera meet the measurement requirements, are full well capacity, Signal to Noise Ratio (SNR), and dynamic range (DR) specifications.  Interpreting these values from specification sheets can be challenging though.  The full well capacity and SNR definitions that are used for the image sensor do not always match those that are used in the specification sheets of the resulting industrial camera. Dynamic range in particular can be confusing as there are different ways to calculate it. 

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Topics: Image Quality Improvements

Reducing noise and increasing camera frame rate through binning - on sensor binning versus digital binning

Posted by Gretchen Alper on Tue, May 10, 2016

There are always small changes (at no additional product cost) that can be made to increase the performance of your machine vision camera and thus to your overall inspection or metrology system.  Perhaps there are low light levels in the system and you need to improve image quality. Binning which is adding the charge of 2 or more pixels together can both increase signal to noise ratio (SNR) and frame rate. Higher signal-to-noise ratio is achieved due to reduced read noise contributions and adding  signals (pixels) together. By adding pixels together the noise component will be reduced due to averaging. Because fewer pixels are processed with binning, a higher camera frame rate can be achieved to increase the system throughput. 

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Topics: Image Quality Improvements