Hybrid enhancement of infrared night vision imaging system

This paper presents a proposed approach for the enhancement of Infrared (IR) night vision images. This approach is based on a trilateral contrast enhancement in which the IR night vision images pass through three stages: segmentation, enhancement and sharpening. In the first stage, the IR image is divided into segments based on thresholding. The second stage, which is the heart of the enhancement approach, depends on additive wavelet transform (AWT) to decompose the image into an approximation and details. Homomorphic enhancement is performed on the detail components, while plateau histogram equalization is performed on the approximation plane. Then, the image is reconstructed and subjected to a post-processing high-pass filter. Average gradient, Sobel edge magnitude and spectral entropy are used as quality metrics for evaluation of the proposed approach. The used metrics ensure good success of this proposed approach.