Registration of multispectral images with other sensor image such as optical, SAR images, which is the process of estimating the misalignment between two images, is a crucial preprocessing for many applications of multispectral images [1], such as fusion and change monitoring. Recently, some methods have been proposed for multisensory image registration in remote sensing [2]-[5], such as Pixel ...

In the past few years there has been a significant volume of research work carried out in the field of multispectral image acquisition. The focus of most of these has been to facilitate a type of multispectral image acquisition systems that usually requires multiple subsequent shots (e.g. systems based on filter wheels, liquid crystal tunable filters, or active lighting). Recently, an alternati...

Watermarking represents a potentially effective tool for the protection and verification of ownership rights in remote sensing images. Multispectral images (MSIs) are the main type of images acquired by remote sensing radiometers. In this paper, a robust multispectral image watermarking technique based on the discrete wavelet transform (DWT) and the tucker decomposition (TD) is proposed. The co...

This dissertation addresses the advantage of using multispectral narrow-band images over conventional broad-band images for improved face recognition under varying illumination. To verify the effectiveness of multispectral images for improving face recognition performance, three sequential procedures are taken into action: multispectral face image acquisition, image fusion for multispectral and...

Multispectral images contain many clues of surface characteristics of the objects, thus can be widely used in many computer vision tasks, e.g., recolorization and segmentation. However, due to the complex illumination and the geometry structure of natural scenes, the spectra curves of a same surface can look very different. In this paper, a Low Rank Multispectral Image Intrinsic Decomposition m...

In this paper we propose a multispectral image compression based on lossy to lossless coding, suitable for both spectral and color reproduction. The proposed method divides a multispectral image data into two groups, RGB and residual. The RGB component is extracted from the multispectral image, for example, by using the XYZ Color Matching Functions, a color conversion matrix, and a gamma curve....

We have developed a new and innovative technique for combining a high-spatial-resolution multispectral image with a lower-spatial-resolution hyperspectral image. The approach, called CRISP, compares the spectral information present in the multispectral image to the spectral content in the hyperspectral image and derives a set of equations to approximately transform the multispectral image into ...

Methods for fusing multispectral low-resolution remotely sensed images with a more highly resolved panchromatic image are described. The goal is to obtain a high-resolution multispectral image which combines the spectral characteristic of the low-resolution data with the spatial resolution of the panchromatic image. Unlike other applications, e.g. image fusion in military missions or computer-a...

An innovative approach to spectral pattern recognition for multispectral images based on Genetic Programming is introduced. The problem is faced in terms of unsupervised pixel classification. The system is tested on a multispectral image with 31 spectral bands and 256 · 256 pixels. A good quality clustered output image is obtained.

Two promising technologies have been developed to improve image acquisition, namely high dynamic range (HDR) and multispectral imaging. In HDR imaging, several RGB images acquired with different exposures are combined into one image with greater dynamic range. This reduces saturated and underexposed image areas and improves the signal-to-noise ratio (SNR) of the image. On the other hand, multis...