How to evaluate the sensitivity of a camera (1)
Basic camera specifications,such as frame rate,resolution,and interface,are relatively easy to implement;However,comparing the imaging performance of cameras,such as quantum efficiency,temporal dark noise,and saturation capacity,is not so simple.Firstly,we need to understand what these different measurements truly mean.
What is quantum efficiency?Is it measured at peak wavelength or a specific wavelength?What is the difference between signal-to-noise ratio and dynamic range?This article introduces how to compare and select cameras using imaging performance data that follows the EMVA1288 standard.
The EMVA1288 standard defines various aspects of measuring camera performance,how to measure them,and how to present these measurement results in a unified way.Here,we will first introduce some basic concepts that are crucial for understanding how image sensors convert light into digital images and ultimately determine sensor performance.Taking a single pixel as an example,these concepts are highlighted in Figure 1.
Firstly,it is necessary to understand the inherent noise of light itself.Light is composed of discrete particles and photons,generated by a light source.Because the light source randomly generates photons,there will be noise in the intensity of the light.Photophysics believes that the noise observed in light intensity is equivalent to the square root of the number of photons produced by the light source.This type of noise is called shot noise.
It should be pointed out that the number of photons observed from a pixel will depend on exposure time and light intensity.This article views photon count as a combination of exposure time and light intensity.Similarly,there is a non-linear relationship between pixel size and the light collection ability of the sensor,as pixel size needs to be squared before it can be used to determine the photosensitive area.
The first step in digitizing light is to convert photons into electrons.This article will no longer elaborate on how sensors complete this conversion,but instead introduce the measurement of conversion efficiency.The ratio of electrons to photons generated during the digitization process is called quantum efficiency(QE).The quantum efficiency of the sensor shown in Figure 1 is 50%,as 6 photons"fall"on the sensor,producing 3 electrons.
Before electrons were digitized,they were stored within pixels,known as traps.The number of electrons that can be stored in a well is called saturation capacity or well depth.If the trap receives more electrons than its saturation capacity,the additional electrons will not be preserved.
Once the pixel completes the collection of light,the charge in the trap is measured,which is called a signal.The signal measurement in Figure 1 is displayed using a pointer type instrument.The error associated with this measurement is called temporal dark noise or readout noise.Finally,the grayscale level is determined by converting the signal value(expressed electronically)into the pixel value of a 16 bit analog-to-digital converter unit(ADU).The ratio between the analog signal value and the digital grayscale value is called gain and measured in terms of the number of electrons per ADU.Do not confuse the gain parameters defined by the EMVA1288 standard with the gain during the analog-to-digital conversion process.
When evaluating camera performance,signal-to-noise ratio and dynamic range are usually referred to.The measurement of these two aspects of camera performance needs to consider the ratio between signal and camera noise.The difference is that the dynamic range only considers temporal dark noise,while the signal-to-noise ratio also considers the sum of root mean square of shot noise.
The absolute sensitivity threshold is the number of photons that equate a signal to noise generated by the sensor.This is an important indicator as it represents the minimum amount of light theoretically required to observe any meaningful signal.
