Small-target judging method based on the effective image pixels for measuring infrared radiation characteristics

Area of Science:

• Infrared imaging and target characterization.
• Optical engineering and system analysis.

Background:

• Accurate target classification is crucial for infrared radiation measurements.
• Distinguishing between small and surface targets is a key challenge in imaging systems.

Purpose of the Study:

• To propose and validate a method for judging whether a target is small or surface-based.
• To account for the influence of imaging system diffusion and signal-to-noise ratio (SNR) in target classification.

Main Methods:

• Development of a discrete imaging process model to simulate small target images.
• Implementation of an algorithm to estimate effective imaging pixels.
• Establishment of judgment criteria based on a threshold number of effective imaging pixels.

Main Results:

• Characteristic curves for target judgment were obtained.
• A clear criterion was established: targets with fewer effective imaging pixels than the threshold are classified as small targets.
• Experimental validation confirmed the method's feasibility and effectiveness.

Conclusions:

• The proposed method provides a reliable approach for classifying targets as small or surface-based in infrared imaging.
• Effective imaging pixels, influenced by system diffusion and SNR, are key indicators for target classification.
• This technique enhances the accuracy of infrared radiation characteristic measurements.