Título: Visible and Infrared Image Fusion Using the Lifting Wavelet
Autores: Zou, Yuelin; Shijiazhuang Information Engineering Vocational College
Liang, Xiaoqiang; Shijiazhuang Information Engineering Vocational College
Wang, Tongming; Hengshui University
Fecha: 2013-11-01
Publicador: TELKOMNIKA: Indonesian journal of electrical engineering
Fuente:
Tipo: info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Tema: image processing;Electronics and Computer Engineering
Image fusion, weighted average;Lifting Wavelet
Descripción: In recent years image fusion plays a vital role in the image processing area. Fused images would help in doing many applications in image processing like segmentation, image enhancement and many.In order to improve the effect of fusion visible and infrared image images of the same scene, this paper presents an image fusion method based on lifting wavelet domain. Firstly, the source images are decomposed using lifting wavelet domain transform (LWT). Secondly, a weighted average approach based on normalized Shannon entropy is used to fuse low frequency lifting wavelet coefficients of the visible and infrared images. The fusion rule of local energy maximum is used to combine corresponding high frequency coefficients. After fusing low and high frequency coefficients of the source images, the final fused image is obtained using the inverse LWT. The experiments show that the proposed method provides improved subjective and objectives results as compared to previous image fusion methods such as Laplacian transform and traditional Wavelet transform.
Idioma: Inglés