Multi-Sensor Fusion based on DWT, Fuzzy

Histogram Equalization for Video Sequence

Nada Habeeb¹, Saad Hasson², and Phil Picton³

¹Technical College of Management, Middle Technical University, Iraq

²Department of Computer Science, College of Science, University of Babylon, Iraq

³School of science and Technology, University of Northampton, UK

Abstract: Multi-sensor fusion is a process which combines two or more sensor datasets of same scene resulting a single output containing all relevant information. The fusion process can work in the spatial domain and the transform domain. The spatial domain fusion methods are easy to implement and have low computational complexity, but they may produce blocking artefacts and out of focus which means that the fused image got blur. In this paper, fusion algorithm has been proposed to solve this problem based on Discrete Wavelet Transform (DWT), Fuzzy Histogram Equalization, and De-blurring Kernel. In addition, two fusion techniques: Maximum selection and weighted average were developed based on Mean statistical technique. The performance of the proposed method has been tested on the real and synthetic datasets. Experimental results showed the proposed fusion method with traditional and developed fusion rules gives improvement in fused results.

Keywords: Multi-sensor fusion, discrete wavelet transform, fuzzy histogram equalization, de-blurring kernels, principle component analysis.