Histogram-based Self-adaptive Segmented Linear Method of Grayscale Transformation for Infrared Images

摘要

In view of the high noise and contrast of the images of infrared temperature measurement in the environment of high temperature, high dust and high air flow, this paper proposes a linear method of grayscale transformation with the statistical method of grayscale histogram and according to the principle of "the display of narrow space areas by the grayscales of infrared images", so as to find out two wave valleys with the maximum grayscale area from the perspectives of high and low grayscales respectively, and use them as segmented transformation points to stretch and suppress different grayscale ranges of infrared images. As shown by the experimental results, in the high-noise environment, the enhancement effect of infrared images is obvious, the grayscales are uniform, the image details can be maintained desirably, and the computational efficiency of the algorithm is high.