1. What is Flicker

In the field of automotive imaging, Flicker refers to the phenomenon of periodic brightness fluctuations, banding, or local brightness instability in images captured by a camera. This phenomenon is not the “flicker visible to the naked eye” from the light source, but rather a visible capture deviation of the “periodic brightness changes” of the light source caused by a mismatch between the periodic characteristics of the camera and the light source. In ADAS applications, flicker increases the difficulty of recognizing traffic signals, speed signs, or safety information.

The flicker phenomenon is essentially a problem caused by temporal sampling mismatch. LED lights typically emit light in pulses at a frequency of hundreds of times per second, and their apparent brightness is controlled by adjusting the duty cycle of the pulses (i.e., the proportion of the on-time within a single cycle). Since the human eye acts as a natural temporal low-pass filter, these high-frequency pulses are visually “smoothed” into a continuous and stable light effect, so the LED light appears to be constantly on to the human eye. However, a camera capturing the light source may expose at the same time scale as these fluctuations, making it more likely for the camera to capture the dynamic changes of the light source itself.

As shown in Figure 1, when a traffic light appears continuously on to the human eye, the camera captures alternating “on” and “off” states of the traffic light. This occurs because flicker happens when the exposure time in consecutive frames does not overlap with the LED light pulses, and is detected by the camera. This directly prevents the camera from accurately reproducing the actual state of the traffic signal, resulting in a significant deviation between its recognition results and the true state perceived by the human eye.

2. Types of Flicker

In automotive imaging applications, LED flicker mainly involves two application scenarios:
1. Illuminant Flicker
Flicker of directly imaged light sources within the camera's field of view, such as headlights, traffic signals, or road signs, is referred to as “Illuminant flicker”.

2. Reflectance Flicker
Flicker occurring in image areas illuminated by a flickering light source, such as the flicker presented by surface reflections when light illuminates the road, is referred to as “Reflectance flicker”.

3. How to Measure Flicker
3.1 Test Standards:
Flicker testing is based on the IEEE 2020-2024 standard.

3.2 Test Equipment:
The self-developed MLB-HMC ADAS Camera Comprehensive Tester by Yanding is specifically designed for ADAS camera image quality testing. It can evaluate imaging quality under complex lighting environments and various motion conditions, and can be used for CPI, Flicker, and Motion testing of ADAS cameras. Its dedicated software control system ensures high consistency of test conditions, allowing efficient measurement by importing scripts after a single setup, making it suitable for horizontal performance comparison of cameras.

3.3 Environment Setup:
“Illuminant flicker”: Where 1 is the uniform neutral background, 2 is the background illumination light source, 3 is the DUT, 4 is the baffle, and 5 is the LED light source.

“Reflectance flicker”: Where 1 is the uniform neutral background, 2 is the modulated light source, 3 is the DC light source, 4 is the baffle, and 5 is the DUT.

3.4 Video Acquisition:
According to the test requirements, parameters related to test conditions such as the frequency, brightness, and flickering time of the LED light are controlled via software scripts. Once set up, video recording can begin.

3.5 RIQA Analysis:

1. Open the RIQA software, select FlickerIn for illuminant flicker, and select FlickerOut for reflectance flicker. Click the “+ Add” button to import the video to be analyzed. The right menu will display and allow you to set the specific coordinate information of the ROI box, and the ROI can be fine-tuned. After selection, click Start.

2. The software automatically analyzes and generates a detailed test report containing specific data and plots for metrics such as Flicker Modulation Index (FMI), Modulation Mitigation Probability (MMP), and Flicker Detection Index (FDI).

3.6 Result Interpretation:
1. Flicker In Result Interpretation:

The larger the FDI and MMP values, the lower the “degree” of flicker. FBF generally maintains different values, but should not be too small, in order to cover various scenarios.

2. Flicker Out Result Interpretation: