This question hits the nail on the headinfrared thermal imagerThe core contradiction of design, balancing pixels and sensitivity, is to find a technically optimal solution between "image details" and "detecting weak heat".

The core conclusion is that there is a natural negative correlation between pixels and sensitivity. On detector chips of the same size, the more pixels there are, the smaller the area of a single pixel, the less infrared radiation energy it can receive, and the sensitivity naturally decreases; On the contrary, the fewer pixels, the larger the area of a single pixel, and the higher the sensitivity, but the image resolution will decrease.

1. Core contradiction: The trade-off between pixels and sensitivity

This contradiction arises from the physical limitations of infrared detectors, which are mainly determined by two factors:

-Pixel Pitch: When the chip size is fixed, the number of pixels doubles and the area of a single pixel is halved. The infrared energy received by a pixel is proportional to its own area. The smaller the area, the less energy it captures, and the weaker its sensitivity to subtle temperature changes.

-Noise impact: The signal strength of small pixels is lower, while the electronic noise of the detector itself is relatively fixed, which can lead to a decrease in signal-to-noise ratio (SNR), ultimately resulting in an increase in image noise and a decrease in temperature resolution.

2. Mainstream balanced technology solutions in the industry

In order to balance both, manufacturers mainly achieve optimization through the following three technological paths:

Option 1: Optimize detector materials and structure

-Use higher performance infrared materials such as mercury cadmium telluride (MCT) or indium gallium antimonide (InGaSb), which have higher absorption efficiency for infrared radiation and can maintain high sensitivity even at small pixel sizes.

-Adopting a Microbolometer structure improvement, such as increasing the thickness of the thermal isolation layer of pixels, reducing heat loss, and enhancing the thermal response efficiency of individual small pixels.

Option 2: Signal processing algorithm compensation

-Pixel Binning technology: In detecting weak signal scenes, adjacent 2x2 or 4x4 pixels are merged into one "large pixel", which is equivalent to temporarily increasing the pixel area and improving sensitivity; Switch back to normal mode when high resolution is required.

-Noise Reduction Algorithm (NR): By using algorithms such as multi frame overlay and adaptive filtering, excess noise caused by small pixels is removed, improving the purity and temperature resolution of the image without changing the hardware.

Option 3: Targeted design based on application scenarios

This is the most direct way to balance, which is to prioritize ensuring a certain performance based on user needs:

-Priority sensitivity: For scenarios such as power inspection and night vision security, if it is necessary to detect distant or weak heat (such as local overheating of equipment or hidden targets), models with lower pixels (such as 384x288) but higher sensitivity will be selected.

-Priority pixel (resolution): For industrial inspection and medical diagnosis scenarios, where it is necessary to observe the details of the target (such as circuit board solder joints, skin blood vessel distribution), high pixel (such as 1280x1024) models will be selected, while compensating for the loss of sensitivity through material upgrades.

3. Judgment criteria in actual selection

in the selectioninfrared thermal imagerAt this time, there is no need to pursue the highest pixel and sensitivity, but to judge based on core requirements:

1. Look at the detection distance: Long distance detection (such as 100 meters away) requires higher sensitivity, and high pixel count can lead to blurry images due to weak signals.

2. Check the size of the target: High pixel detection is required for small targets (such as electronic components), while sensitivity can be prioritized for detecting large targets (such as building exterior walls).

3. Check the ambient temperature: In low temperature environments (such as minus tens of degrees) or scenes with extremely small temperature differences, sensitivity is much more important than pixels.