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Bi-dimensional Empirical Mode Decomposition Based Contrast Enhancement Technique for UAV Thermal Images

In this paper, a new contrast enhancement technique based on bi-dimensional empirical mode decomposition (BEMD) is proposed to enhance the target details in low contrast thermal images captured by unmanned aerial vehicle (UAV). Initially, thermal image acquired from UAV is separated into intrinsic mode functions (IMFs) and residue using BEMD. Then, local standard deviation based method is employed to the IMFs to improve the details of the image and histogram modification function is employed to the residue to enhance the contrast. The processed IMFs and residue are reconstructed to obtain the enhanced image using inverse BEMD. The performance of the proposed technique is analysed using quantitative and visual quality measures with the well-known histogram equalization, dynamic range partitioning and wavelet-based enhancement methods. Experimental results demonstrate that the proposed technique effectively enhances the contrast and details in the image with less noise and visual artefacts than other methods.