Abstract
A generalized wavelet domain image fusion method which imposes weights on each of the wavelet coefficients for improving the conventional wavelet domain approach is pre- sented. The weights are controlled in the least-squares sense for enhancing the details while suppressing excessive high frequency components. In experiments with IKONOS and QuickBird satellite data, we demonstrated that the proposed method shows a comparable or better performance than conventional methods in terms of various objective quality metrics. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original pub- lication, including its DOI. (DOI: 10.1117/1.JRS.8.080599)
Highlights
Various image fusion techniques have been developed to obtain a high-resolution multispectral (HRM) satellite image from a set of sensor data: a high-resolution panchromatic (HRP) image containing only intensity information and several low-resolution multispectral (LRM) images with color information.[1]
Otazu et al.[4] proposed a method in which the wavelet plane of the HRP image is added to each LRM image in proportion to its color intensity value [additive wavelet (AW)-luminance proportional (AWLP)], whereas Kim et al.[5] proposed to add the difference between the wavelet planes of HRP image and each LRM image with or without considering the relative radiometric signature of the LRM images [improved AW (IAW) and IAW proportional (IAWP)]
The reference HRM images are compared to the HRM images which are obtained by fusing the degraded HRP and LRM images from the original satellite images to 4 and 16-m resolution, respectively
Summary
Various image fusion techniques have been developed to obtain a high-resolution multispectral (HRM) satellite image from a set of sensor data: a high-resolution panchromatic (HRP) image containing only intensity information and several low-resolution multispectral (LRM) images with color information.[1]. The AW considers the high frequency components of all the LRM images and the HRP image, and possibly introduces excessive high frequency details in the synthesized image. There have been efforts to overcome these drawbacks using some improved wavelet-domain methods utilizing weighted merging.[4,5] Otazu et al.[4] proposed a method in which the wavelet plane of the HRP image is added to each LRM image in proportion to its color intensity value [AW-luminance proportional (AWLP)], whereas Kim et al.[5] proposed to add the difference between the wavelet planes of HRP image and each LRM image with or without considering the relative radiometric signature of the LRM images [improved AW (IAW) and IAW proportional (IAWP)]. The results show that the proposed method does not introduce noticeable color distortion and enhances the details better than the conventional methods
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
