There are often subtle adjustments that can significantly improve the performance of your machine vision camera and, consequently, your overall inspection or metrology system—without incurring extra product costs. For example, if your system operates under low-light conditions, enhancing image quality may be necessary. One effective technique is binning, which involves combining the charge from two or more pixels to increase both the signal-to-noise ratio (SNR) and frame rate.

The improvement in SNR results from two factors: reduced contributions of read noise and the averaging effect when signals (pixels) are combined. By merging pixel data, the noise component decreases due to this averaging process. Additionally, because fewer pixels need to be processed during binning, a higher camera frame rate can be achieved—thereby boosting system throughput.

However, it’s important to note that binning has different implementations: on-sensor (charge domain) and digital. These approaches yield distinct results, as outlined in the table below.

Differences Between On-Sensor and Digital Binning

Feature On-Sensor Binning Digital Binning
Increases SNR via reduced read noise Yes No
Increases SNR via averaging reduction Yes Yes
Improves frame rate Yes No
Reduces interface data volume Yes Yes

When binning is performed in the digital domain, both signal and noise increase. In contrast, on-sensor binning increases the signal while keeping the noise floor unchanged. For low-light imaging scenarios, on-sensor binning often provides a dramatic quality improvement over digital pixel summing.

Figure 1 illustrates this effect: on the left is an image captured at full resolution; on the right is the same scene with 2×2 binning applied. The full-resolution image appears dark and lacks contrast, whereas the binned version is sharp and brighter. Although the resolution of the binned image halves (it covers half as many pixels), its field-of-view remains identical. This demonstrates how binning allows users to trade off resolution for sensitivity—exactly when that might be beneficial.

Additionally, since digitizing a single pixel represents the slowest step in readout sequences, binning can effectively increase frame rates by reducing the total number of pixels processed. However, this improvement is only possible with on-sensor binning: digital binning requires reading out all sensor data first anyway, so it doesn’t provide additional speed gains.

Binning also finds occasional use when optical configurations necessitate larger physical pixel sizes or higher full-well capacities in sensors. For instance, combining pixels (e.g., 100,000 electrons each) into a 2×2 grid results in a new effective capacity of 400,000 electrons—a benefit particularly useful for applications limited by high background illumination and photon shot noise.

Last Updated: 2025-09-04 21:26:35