Detection of Camouflaged People

Abstract

The use of thermal imaging is a benefit for the military people. Due to their advantages, it has a large number of applications, including the detection of camouflaged people. For better results, the thermal information can be merged with the color information which allows a greater de-tail, resulting in a higher degree of security. The present work implemented as pixel level image fusion methods: Principal Components Analysis, Laplacian Pyramid, and Discrete Wavelet Transform. A qualitative analysis concluded that the method which performs better is the one that uses Wavelets, followed by the Laplacian Pyramid and finally the PCA. A quantitative analysis was made using the metrics: Standard Deviation, Entropy, Spatial Frequency, Mutual Information, Fusion Quality Index and Structural Similarity Index. The values obtained support the conclusions extracted from the qualitative analysis.