The present application belongs to the technical field of
image processing, and particularly relates to a
forging process temperature field real-time monitoring method based on
infrared images, which comprises the following steps: firstly, a temperature prediction model is established based on Newton's cooling law; secondly, a spectral selectivity
distortion factor is constructed to quantify environmental interference by comparing the measured and expected
radiation intensity ratios of multi-band
infrared images; at the same time, a surface
emissivity mutation index is constructed to identify surface changes by calculating the space-time gradient of
radiation intensity; finally, the reliability
score of colorimetric temperature is calculated by comprehensively considering the two indexes, and the predicted temperature and the colorimetric temperature are dynamically weighted and fused according to the
score, so as to output an accurate, continuous and strong anti-interference optimal temperature
estimation value. The present application can realize accurate
temperature measurement by constructing environmental interference and surface state change indexes, evaluating the reliability of colorimetric temperature, and dynamically weighting and fusing the colorimetric temperature and the predicted temperature based on a
physical model.