The type of image sensor of a car dash cam is the core factor that determines its shooting performance. Sensors with different technical paths have essential differences in light capture, signal processing, and dynamic response. These differences will be directly reflected in the picture clarity, night vision performance, and the ability to capture moving objects.
At present, the mainstream image sensors are mainly divided into two categories: CCD (charge-coupled device) and CMOS (complementary metal oxide semiconductor). CCD sensors use a global shutter design, which allows the entire picture to be exposed at the same time, with good photosensitivity uniformity, but they have high power consumption, high cost, and low integration, and are gradually replaced by CMOS in the consumer field. CMOS sensors use a rolling shutter with progressive scanning (some high-end models use a global shutter). Each pixel unit has its own independent amplifier, which has the advantages of low power consumption and high integration. In recent years, through the upgrade of back-illuminated and stacked technologies, the comprehensive performance has surpassed CCD in an all-round way, becoming the mainstream choice for car dash cams.
The picture clarity depends not only on the number of pixels of the sensor, but also on the arrangement of pixels and photosensitivity efficiency. Sensors with high pixel density (such as models corresponding to 4K resolution) can capture more details of the picture, but if the pixel size is too small, the amount of light entering a single pixel will be insufficient, which will affect the image quality. In order to balance the resolution and photosensitivity, many sensors use pixel merging technology to merge the photosensitivity signals of adjacent pixels and increase the overall amount of light without reducing the resolution. For example, some sensors use four-in-one pixel technology to allow small-size pixels to simulate the photosensitivity effect of large pixels in low light, so that the picture is rich in details during the day and the noise at night can be effectively controlled.
The key to the night vision effect lies in the photosensitivity of the sensor in low-light environments. A larger photosensitive area (i.e., the size of the sensor target surface) means that a single pixel can receive more light, which can significantly improve the light capture efficiency when combined with back-illuminated technology (moving the circuit behind the pixel to reduce occlusion) or stacked structure (separating the photosensitive layer and the logic circuit). This type of technology allows the sensor to reduce picture noise in dimly lit environments (such as streets at night and underground garages), retain more dark details, and avoid blurring or color cast due to underexposure. On the contrary, small-size sensors are prone to a surge in image noise or even large-area blur due to insufficient photosensitivity in low light.
The ability to capture motion is mainly reflected in the sensor's ability to clearly record fast-moving objects and retain details under complex light. The global shutter sensor can achieve synchronous exposure of the entire screen, effectively avoiding the "jelly effect" (distortion of the screen caused by progressive scanning exposure), which is suitable for capturing fast dynamic scenes such as sudden braking and vehicle lane changes. The edges of objects in the screen are clear and there will be no smear or deformation. However, the rolling shutter sensor may distort the screen when shooting high-speed moving objects, affecting the restoration of details. In addition, high dynamic range (HDR) technology can balance the exposure of strong light and shadow areas through multi-frame synthesis, so that the vehicle license plate and the surrounding environment can be clearly seen in scenes with strong light and dark contrasts such as tunnel entrances and bridge shadows.
When the sensor works for a long time, it will generate noise due to heat, affecting the purity of the picture, especially in high temperature environments. CMOS sensors can effectively reduce the generation of thermal noise by optimizing pixel circuit design and chip heat dissipation structure. For example, some sensors integrate advanced noise reduction algorithms, which can maintain the stability of image quality during long-term shooting by processing noise in the picture in real time. However, due to technical limitations, the early CCD sensors had weak thermal noise control capabilities. After long-term use, the picture may have obvious graininess, affecting the viewing experience.
Modern car dash cams often work together with sensor hardware through software algorithms to further improve the shooting effect. For example, the intelligent defogging algorithm can enhance the picture contrast in haze weather, and the motion detection algorithm can automatically optimize the clarity of moving objects. These algorithms need to rely on the quality of the original data provided by the sensor: sensors that support RAW format output can retain more original photosensitive information and provide more space for post-processing algorithm processing, while pre-processed sensor data may affect the algorithm effect due to loss of details. Therefore, sensors with excellent hardware performance combined with targeted algorithm optimization can significantly improve the practicality of the picture in complex scenes (such as rainy days and strong light).
When choosing a car dash cam, users can focus on features such as sensor type (new CMOS is preferred), photosensitive area (larger target surface usually has better performance), whether HDR and global shutter are supported, etc. Current technology trends show that global shutter CMOS is gradually being applied to mid-range products, and sensors based on new materials (such as quantum dot technology) are also under development, which may further improve the shooting capabilities in full-light environments in the future. It is recommended to select an adapted model based on the actual usage scenario (such as urban commuting, night driving frequency), and pay attention to the firmware upgrade support of the product to ensure that the sensor performance can continue to play a role through software optimization.
The technical characteristics of the image sensor comprehensively affect the core performance of the car dash cam through dimensions such as photosensitivity efficiency, signal processing and dynamic response. Only by understanding these differences and selecting models based on actual needs can the device record key images clearly and reliably in various environments.
