Bispectral image fusion using multi-resolution transform for enhanced target detection in low ambient light conditions

Abstract

Performing target detection/identification task using only visible spectrum information becomes extremely difficult during low ambient light conditions. Visible spectrum information consists of information available in the range of 400-700 nm wavelength. However, infrared spectrum carries information beyond 800 nm. To overcome the difficulty of target detection by human operator during the task of surveillance, fusion of visible and infrared spectral image information has been proposed. The image fusion has been performed using multi resolution transform based curvelet technique. The use of curvelet transform has been done because of its high directional sensitivity and reconstruction quality. Curvelet transform has been used to decompose source images to obtain coefficients at coarse, intermediate and fine scale. These coefficients have been fused as per respective decomposition level, followed by reconstruction of fused image using inverse curvelet transform. Bispectral fused image inherits scene information as well as target information both from visible and infrared spectrum images respectively. The proposed image fusion output images are visually and statistically compared with other fusion method outputs. The fused image obtained using proposed fusion method in comparison to other fusion results show clear background details, high target distinctiveness, better reconstruction and lesser clutter.