2010/07/05 by Mrinal Kanti Bhowmik, Debotosh Bhattacharjee, Bhowmik, Mrinal Kanti +7
Computer Science · Engineering · #Advanced Image Fusion Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #Remote-Sensing Image Classification #cs.CV
paper · pdf · doi:10.48550/arxiv.1007.0621
arxiv created 2010/07/05 · openalex publication_date 2010/07/05 · arxiv updated 2010/07/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper fusion of visual and thermal images in wavelet transformed domain has been presented. Here, Daubechies wavelet transform, called as D2, coefficients from visual and corresponding coefficients computed in the same manner from thermal images are combined to get fused coefficients. After decomposition up to fifth level (Level 5) fusion of coefficients is done. Inverse Daubechies wavelet transform of those coefficients gives us fused face images. The main advantage of using wavelet transform is that it is well-suited to manage different image resolution and allows the image decomposition in different kinds of coefficients, while preserving the image information. Fused images thus found are passed through Principal Component Analysis (PCA) for reduction of dimensions and then those reduced fused images are classified using a multi-layer perceptron. For experiments IRIS Thermal/Visual Face Database was used. Experimental results show that the performance of the approach presented here achieves maximum success rate of 100% in many cases.