Clinical MRI data is normally corrupted by random noise from the measurement process which reduces the accuracy and reliability of any automatic analysis. For this reason, de-noising methods are often applied to increase the SNR and improve image quality. Most of these methods work on single channel images by correcting each grey level using an implicit model of the surrounding region, but with...

hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. however, the stochastic data analysis approaches that have been successfully applied to multispectral data are not as effective for hyperspectral data as well. various investigations indicate that the key problem that causes poor performance in the stochastic approaches t...

In the last few years multispectral imaging has entered the field of painting diagnostics and conservation because of its effectiveness and safety. It provides spectral and colorimetric characterization of the whole paint layer, suitable to document the conservation state of the artwork and useful in the study for the identification of pigments. Here we present a high-resolution scanning system...

The aim of biometrics is to identify humans from their personal traits more efficiently using devices, algorithms and procedures for applications that require security and authentication. Multispectral image analysis has gained importance due to its potential for accurate and faster recognition performance. In this paper, Multispectral palmprint biometric system is proposed which uses the fusio...

For scaling up low resolution multispectral images (LRMIs) with high resolution panchromatic image (HRPI), intensity-hue-saturation (IHS) can produce satisfactory spatial enhancement but usually introduces spectral distortion in the fused high resolution multispectral images (HRMIs). In this paper, to minimize this problem, we present a generalized intensity modulation (GIM) by extending the IH...

Intensity-Hue-Saturation (IHS) and Principal Component Analysis (PCA) are two famous methods to which image fusion algorithms can be reported when merging panchromatic (Pan) and multispectral (MS) images, acquired with different spatial and spectral resolutions. The IHS is a wellknown pan-sharpening approach widely used for its efficiency and high spatial resolution. However, it can distort the...