Key Factors Affecting the Accuracy of Thermal Imaging

Thermal imaging technology is based on the infrared radiation emitted by a target object. Through a multi-stage process—including radiation transmission in the atmosphere, detector reception, photoelectric conversion, digital processing, and image optimization—the thermal distribution of the target is visualized.

This process involves several critical steps: radiation generation, transmission, and reception. The accuracy of detection is restricted by multiple factors, and any variation in these conditions may reduce image quality or measurement precision.

Therefore, when evaluating how accurate is thermal imaging, it is essential to recognize that results depend on a combination of factors. In the following sections, we analyze the main influences systematically, including target surface characteristics, environmental and atmospheric conditions, device performance parameters, and methods of operation.

1) Influence of Surface Emissivity

The emissivity of a target’s surface is a core parameter that determines the intensity of its infrared radiation. Under the same temperature conditions, objects with different emissivity levels emit significantly different amounts of radiation, which directly affects the performance of thermal imaging devices. Generally, objects with higher emissivity generate stronger infrared signals at the same observation distance, resulting in clearer surfaces in the thermal image. Conversely, low-emissivity objects are harder to detect.

Emissivity is influenced by multiple factors, including material properties, surface roughness, oxidation level, and color. Even the same object may have different emissivity values under varying temperatures and wavelengths. These variations are a major source of measurement errors in infrared thermography. For example, most non-metallic materials—especially metal oxides—tend to have high emissivity, while pure metals usually have low emissivity. Surface roughness also plays a significant role: rougher surfaces reflect less, thereby increasing emissivity, which is especially evident in metallic materials.

In addition, emissivity is direction-dependent, particularly for polished or smooth surfaces. To measure the true temperature of an object with emissivity lower than 0.9, the thermal camera should ideally be positioned perpendicular to the surface. If that is not possible, the measurement angle should remain within 30° of the surface normal. Otherwise, emissivity parameters need to be corrected accordingly.

Understanding how emissivity affects readings is crucial when evaluating how accurate is thermal imaging, since inaccurate emissivity settings often lead to temperature deviations or misinterpretations.

1) Impact of Atmospheric Conditions

Atmospheric transmittance is an important indicator used to evaluate how the atmosphere affects infrared radiation. It is defined as the ratio between the attenuated infrared energy that passes through the atmosphere and the original radiation emitted by the target. Gases such as nitrogen, oxygen, carbon dioxide, and water vapor absorb and scatter infrared radiation to varying degrees, which reduces the intensity of the signal. This attenuation decreases the ability of thermal imaging devices to collect signals, thereby affecting detection results.

Under extreme weather conditions, such as heavy rain or snowfall, infrared radiation transmission is further impacted. When raindrops are dense, infrared signals cannot travel in a straight path; instead, scattering and absorption occur, leading to signal loss. During snowfall, snowflakes cause both reflection and scattering, which not only introduces interference but also absorbs and diminishes infrared radiation, resulting in lower image quality. Similarly, fog, hail, and other adverse weather conditions significantly reduce thermal imaging performance.

2) Impact of Ambient Temperature

The surrounding temperature also influences the actual temperature of the measured target, which in turn affects measurement accuracy. In high-temperature environments, the target may heat up, causing readings to appear higher than the real value. Conversely, in low-temperature environments, the measured value may be underestimated. Therefore, when considering how accurate is thermal imaging, it is important to account for ambient temperature conditions to ensure reliable and precise results.

1) Infrared Resolution

Infrared detector resolution refers to the number of effective pixels in the infrared detector, usually expressed as “horizontal pixels × vertical pixels” (e.g., 256×192, 384×288, 640×512, 1280×1024). The higher the resolution, the more temperature points can be captured within a unit area, resulting in clearer images with richer details. Conversely, lower resolution produces blurry images with insufficient detail, reducing target recognition capability.

2) Spatial Resolution (IFOV)

Spatial resolution, also known as Instantaneous Field of View (IFOV), represents the smallest distance between two objects that a thermal imaging device can distinguish, typically measured in milliradians (mrad). It is determined by the pixel pitch of the detector and the focal length of the lens. With a fixed focal length, smaller pixel pitch increases the number of pixels, thereby enhancing image detail and clarity. With fixed pixel pitch, higher spatial resolution means a longer focal length, which narrows the field of view but improves magnification and image sharpness. At a constant target distance, higher spatial resolution allows the camera to capture finer details, making the image clearer.

3) Thermal Sensitivity (NETD)

Thermal sensitivity, also called Noise Equivalent Temperature Difference (NETD), indicates the smallest temperature difference a thermal camera can detect between the target and the background, usually expressed in millikelvins (mK). NETD is influenced by factors such as lens optics (F-number), detector type, integration time, and operating temperature. A lower NETD value means the device can detect smaller temperature differences, producing higher image contrast and finer details—especially advantageous in low-contrast or weak heat source environments.

4) Field of View (FOV)

The field of view is the angular extent of the observable scene. A wider FOV allows the camera to cover a larger detection area, but because the number of pixels remains constant, pixel density decreases, leading to lower image resolution and less detail. Conversely, a narrower FOV corresponds to a longer focal length, which reduces the covered area but increases pixel density and resolution, producing clearer and more detailed images.

5) Frame Rate

Frame rate refers to the number of frames or images displayed per second, measured in hertz (Hz). In thermal imaging, it represents how many infrared frames are shown per second—commonly 25Hz, 30Hz, or 50Hz. A higher frame rate provides smoother video, especially when observing fast-moving targets, where it helps capture movement more accurately and reduces image lag or motion blur.

When evaluating how accurate is thermal imaging, device performance factors such as resolution, IFOV, NETD, FOV, and frame rate play a critical role in determining both measurement precision and image quality.

Thermal imaging technology visualizes temperature distribution by capturing the infrared radiation emitted by objects, providing precise and efficient temperature measurement for industrial inspections, security monitoring, scientific research, and other applications. However, measurement accuracy is influenced by multiple factors, including the target’s surface characteristics, atmospheric and environmental conditions, and the performance of the thermal camera itself.

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