10TH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, WAVELET AND APPLICATIONS, Kocaeli, Türkiye, 18 - 20 Ekim 2019, ss.16-21
Inspection of an object or a scene using more than one sensor and capturing images at the different
wavelengths of the spectrum provide much more valuable information from the object or scene. Evaluation of the
data becomes more complex while the number of spectral bands are increased, hence the idea of fusing images
obtained at different wavelengths is emerged. The aim of multispectral image fusion is the combination of the
information existed in different bands to enhance the complementary features. Fused image obtained by combining
the images captured at two or more bands, becomes more useful for many applications such as face recognition.
In this paper, face images obtained from LDHF (long distance heterogeneous face) database are fused with discrete
wavelet transform, Laplacian pyramid and cross bilateral filter methods. Results are compared with edge quality
(QE), spatial frequency (SF), fusion factor (FF) and variance weighted structural similarity measure (Qy) metrics.
Experimental results show that, LP and DWT methods are better than CBF in terms of both objective and visual