This paper proposes a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning. By combining the spectral information from sensors with low spatial resolution but high spectral resolution (LSHS) and the spatial information from sensors with high spatial resolution but low spectral resolution (HSLS), this m...

Image fusion is a method for obtaining a highly informative image by merging the relative information of an object obtained from two or more image sources of the same scene. The satellite cameras give a single band panchromatic (PAN) image with high spatial information and multispectral (MS) image with more spectral information. The problem exists today is either PAN or MS image is available fr...

With the development of remote sensing technology, remote sensed data provide detailed information of structure and spectral about ground scenes. However, the traditional classification methods only take objects’ spectral information into consideration but neglect their structural information. There are two major reasons for this: First, the multi-spectral data contain a lot of information on t...

Image fusion is one of the important techniques to enhance image information of remote sensing. In order to adequately make use of all kinds of remote sensing images information such as Panchromatic and threeband multi-spectral images, a novel remote sensing image fusion scheme based on wavelet transform is proposed. The fusion of multispectral (MS) and panchromatic (PAN) images, with complemen...

Recent theoretical work in “compressed sensing” can be exploited to guide the design of accurate, single-snapshot, static, high-throughput spectral imaging systems. A spectral imager provides a three-dimensional data cube in which the spatial information of the image is complemented by spectral information about each spatial location. In this paper, compressive, single-snapshot spectral imaging...

Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Smoothing-FilterBased-Intensity Modulation (SFIM) algorithms were used to pansharpen GeoEye-1 imagery. The pansharpened images were then segmented in Berkeley Image Seg using a wide range of segmentation parameters, and the spatial and spectral accuracy of image segments was measured. We found that pansharpening algorithms that preserve...

Multispectral images such as multispectral chemical images or multispectral satellite images provide detailed data with information in both the spatial and spectral domains. Many segmentation methods for multispectral images are based on a per-pixel classification, which uses only spectral information and ignores spatial information. A clustering algorithm based on both spectral and spatial inf...