-
产品中心
计算机视觉硬件工业相机 镜头 机器视觉光源 采集卡 线材 配件 网络和外围设备计算机视觉软件pylon Camera Software Suite VisualApplets 其他软件产品线嵌入式视觉产品线 医疗和生命科学产品线 CoaXPress产品线面阵相机Basler ace 2 Basler ace Basler MED ace Basler boost Basler beat Basler dart Basler pulse Basler scout线阵相机Basler racerBasler racerBasler racer - the right choice镜头固定焦距镜头机器视觉光源Basler相机光源系列
- 选型工具
- 解决方案
- 下载中心
- 品牌中心
- 销售与支持
-
Vision Campus
相机技术Sony IMX CMOS芯片系列型号比较 为什么要对相机进行色彩校准? 专家教您如何为视觉系统找到合适的镜头 适用于嵌入式视觉系统的五大专家级技巧 什么是多光谱成像? CMOS相机比较 图像处理过程中的色彩 处理板 什么是图像处理 图像处理中的3D技术 什么是嵌入式视觉? 为何选择CMOS图像芯片? 什么是ToF (Time-of-Flight)? 什么是成像质量? 相机尺寸 数字相机的工作原理是什么? 芯片技术:CMOS与CCD的对比 实时性 NIR: 即使在弱光条件也可以呈现清晰图像 高灵敏度图像处理相机显示更多收起接口和标准System Setup with CoaXPress 2.0 什么是CoaXPress? 哪一款接口适合嵌入式视觉? 配备GigE 2.0的多相机系统 USB 3.0 – 引领未来的标准化接口 接口是什么? Camera Link 千兆网(GigE) GenICam标准 USB 3.0和USB3 Vision
- 公司概况
What is sensitivity and why are sensitivity statements often misleading?
Sensitivity
The response curve for a light sensitive sensor can be divided into three parts: the dark area, the linear area and the saturation area. A typical response curve is shown in the graph below.
The dark area of the response curve shows the sensor's response to very low light. The output of the sensor in the dark area is very low, is noisy and is unpredictable. As you gradually increase the light falling on a sensor, you will find a point where the output of the sensor begins to increase predictably as the amount of light increases. This point is called the Noise Equivalent Exposure (NEE).
After the NEE point is reached, the output of the sensor becomes linear. The output remains linear until a point called the Saturation Equivalent Exposure (SEE) is reached. At this point, increasing the light intensity results in a nonlinear increase in the sensor output.

The gradient of the linear portion of the sensor's response curve is commonly referred to as sensitivity and is usually measured in V/µJ/cm2. The higher a sensor's output voltage is for a given amount of light, the higher its sensitivity.
But when you are discussing sensors, talking about sensitivity alone does not make sense. For one thing, NEE is also very important. Since a sensor with a high NEE will be blind at low light levels, NEE should be as low as possible.
Another point to consider is that a digital camera is a system and that sensor sensitivity is just one of the factors involved in the output signal from the camera. Electronic devices in the camera such as Analog to Digital converters and amplifiers also influence the output signal. At Basler, we feel that a camera's "responsivity" is a better measure of camera performance. We also think that since our cameras are digital, responsivity should be stated as DN/µJ/cm2 (DN stands for digital number). The graph below shows a responsivity curve.

If a camera provides a gain feature as most of them do, responsivity will depend on the gain setting. And responsivity really only makes sense when it is stated in combination with a measurement of the camera's noise such as peak-to-peak, signal-to-noise ratio.
Let's consider an example. Suppose that you are comparing two cameras and that they have the following specifications:
- Camera One: Responsivity = 1 DN/µJ/cm$(sup:2)$ Noise = 2 DN (peak-to-peak)
- Camera Two: Responsivity = 2 DN/µJ/cm$(sup:2)$ Noise = 5 DN (peak-to-peak)
At first glance, camera two seems better than camera one because its responsivity is higher. However if camera one has a gain feature, we can adjust the gain and increase the responsivity to two. Keep in mind that if we adjust the gain to double the responsivity from one to two, we will also double the noise. Now we have this situation:
- Camera One: Responsivity = 2 DN/µJ/cm$(sup:2)$ Noise = 4 DN (peak-to-peak)
- Camera Two: Responsivity = 2 DN/µJ/cm$(sup:2)$ Noise = 5 DN (peak-to-peak)
Which camera is better? They now both have the same responsivity, but camera one has lower noise. Camera one would be the better choice.
The lesson to be learned from all of this is that sensor sensitivity alone does not tell the entire story and that we should be sure to use similar measuring criteria when we are comparing cameras.