Maximize contrast and compensation lighting of infrared images using the area of the eyes as pattern

In this paper we propose a preprocessing method of infrared imaging (IR) system designed to estimate the infrared radiation at the scene of acquisition. Radiation in the environment is estimated by using the eye area of the individuals present in the scene, to the region of the face is calculated with different metrics which seeks to establish an estimate of the amount of IR radiation. The metrics used correspond to energy, contrast, homogeneity and entropy using the correlation matrix of gray being used in order to characterize and establish IR radiation ranges in which optimal conditions presented images in regard to their characteristics the results obtained show that the eye area used as pattern has features that could be used to estimate changes of IR radiation in the environment, so it can be used to calculate the metrics described above which will serve as input algorithms to maximize contrast and illumination compensation for the purpose of exercising adaptive corrections on image sequences. Also the contrast maximization algorithm and illumination compensation demonstrated adequate corrections on the infrared images compared to corrections made by the art without adaptability is, when IR radiation is estimated by a pattern, however noise components of the image initial produce some corrections made clearer image noise.