Title :
Infrared and Color Visible Image Sequence Fusion Based on Statistical Model and Image Enhancement
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Leshan Teacher´´s Coll., Leshan
Abstract :
A novel fusion method is proposed for image sequence which based on the non-Gaussian statistical modeling of wavelet coefficients and image enhancement in IHS color space of color visible image. Firstly, the original color visible image is transformed into a perceptually decorrelated color space in order to treat the achromatic and chromatic components separately. Then, the achromatic component and infrared image are combined by a statistical fusion method based on dual tree complex wavelet transform (DT-CWT) using the generalized Gaussian distribution (GGD). The means and variances between the fused component and the original achromatic component are matched by a linear remapping for image enhancement. At last, the color space is transformed back into the RGB color space. This method not only have a superior fusion performance but also can effectively produce a high-contrast color fused image with the similar natural characteristics as the original color visible image.
Keywords :
Gaussian distribution; image colour analysis; image enhancement; image sequences; statistical analysis; trees (mathematics); wavelet transforms; color visible image sequence; dual tree complex wavelet transform; fusion method; generalized Gaussian distribution; image enhancement; infrared image; linear remapping; non-Gaussian statistical modeling; wavelet coefficients; Color; Discrete wavelet transforms; Gaussian distribution; Humans; Image enhancement; Image fusion; Image sequences; Infrared image sensors; Infrared imaging; Layout; DT-CWT; image enhancement; image fusion; statistical model;
Conference_Titel :
Advanced Computer Theory and Engineering, 2008. ICACTE '08. International Conference on
Conference_Location :
Phuket
Print_ISBN :
978-0-7695-3489-3
DOI :
10.1109/ICACTE.2008.69