In real time remote sensing it is necessary to know the quality of images obtained from the different satellite sensors. Pan-sharpening enhances the spatial information of input raw multispectral images. This paper focuses on the evaluation and analysis of eight frequently used image quality assessment methods to determine the preservation of spectral and spatial integrity in the pan-sharpened ...

Abstract— The combined image fusion method which proposed in this paper integrates the information from multiple fusion algorithms which is more suitable for human visual perception. Multispectral images (SPOT) have low spatial resolution. So, integrating of low-resolution multispectral and high-resolution panchromatic (IKONOS) images is a technique for improving the spatial quality of multispe...

–In real time remote sensing it is necessary to know the quality of images obtained from the different satellite sensors. Pan-sharpening enhances the spatial information of input raw multispectral images. This paper focuses on the evaluation and analysis of eight frequently used image quality assessment methods to determine the preservation of spectral and spatial integrity in the pan-sharpened...

We report on a volume holographic imaging spectrometer (VHIS) system which allows retrieval of a scene's twodimensional spatial information as well as its spectral information. This is performed using a transmission volume hologram and a simple rotary scanning mechanism. The system has the advantages of high spectral and spatial resolutions and the potential of single-shot, four-dimensional (3D...

Motivation. Multi and Hyperspectral remote sensing imagery provide valuable insights regarding the composition of a scene and significantly facilitate tasks like object and material recognition, spectral unmixing and region clustering, among others [1], [2]. However, current remote sensing imaging architectures are unable to concurrently acquire high spatial and spectral resolution imagery, due...

For a series of multi-source remotely sensed images of the same area, the sensors’ types and the shooting time will be different. Therefore, there will be varying kinds of distortion or noise in the images, especially the features information will be different, resulting incompletely matching in the process of fusion[1]. Most of the existing methods of fusion are unable to achieve a balance bet...

HJ-1-A satellite, developed by China independently, was equipped with two sensors of Hyper Spectral Imager (HSI) and multispectral sensor (CCD). In this paper, we examine the benefits of combining data from CCD data (high-spatial-resolution, low-spectral-resolution image) with HSI data (low -spatial-resolution, high -spectral-resolution image). Due to the same imaging time and similar spectral ...

A novel methodology based on multiscale spectral and spatial information fusion using wavelet transform is proposed in order to classify very high resolution (VHR) satellite imagery. Conventional wavelet-based feature extraction methods employ single windows of a fixed size, which are not satisfactory as the VHR imagery contains complex and multiscale objects. In this paper, spectral and spatia...

Most multispectral remote sensors (e.g. QuickBird, IKONOS, and Landsat 7 ETM+) provide low-spatial high-spectral resolution multispectral (MS) or high-spatial low-spectral resolution panchromatic (PAN) images, separately. In order to reconstruct a high-spatial/high-spectral resolution multispectral image volume, either the information in MS and PAN images are fused (i.e. pansharpening) or super...

High resolution images offer rich contextual information, including spatial, spectral and contextual information. In order to extract the information from these high resolution images, we need to utilize the spatial and contextual information of an object and its surroundings. If pixel based approaches are applied to extract information from such remotely sensed data, only spectral information ...