Abstract
Optical characterization and internal structure of biological tissues is highly important for biomedical optics. In particular for optical clearing processes, such information is of vital importance to understand the mechanisms involved through the variation of the refractive indices of tissue components. The skeletal muscle presents a fibrous structure with an internal arrangement of muscle fiber cords surrounded by interstitial fluid that is responsible for strong light scattering. To determine the refractive index of muscle components we have used a simple method of measuring tissue mass and refractive index during dehydration. After performing measurements for natural and ten dehydration states of the muscle samples, we have determined the dependence between the refractive index of the muscle and its water content. Also, we have joined our measurements with some values reported in literature to perform some calculations that have permitted to determine the refractive index of the dried muscle fibers and their corresponding volume percentage inside the natural muscle.

Abstract
Ubiquitous Internet access is becoming a major requirement for end-users due to the increasing number of services and applications supported over the Internet. Extending the coverage of current Wi-Fi infrastructures installed in companies, universities and cities, has been considered a solution to help in fulfilling this requirement, namely when it comes to wireless and nomadic Internet access. This paper describes and analyses a new and simple solution, called Wi-Fi network Infrastructure eXtension (WiFIX), aimed at extending current Wi-Fi infrastructures. WiFIX is based on standard IEEE 802.1D bridges and a single-message protocol that is able to self-organize the network, and it only requires software changes in IEEE 802.11 access points (APs); no changes to IEEE 802.11 stations are needed. Overhead analysis and experimental results show both the higher efficiency of the solution compared to the IEEE 802.11s draft standard and its good performance as far as data throughput, delay and packet loss are concerned. Copyright (C) 2010 John Wiley & Sons, Ltd.

Abstract
This paper describes an approach based on the shortest path method for the detection and tracking of vibrating lines. The detection and tracking of vibrating structures, such as lines and cables, is of great importance in areas such as civil engineering, but the specificities of these scenarios make it a hard problem to tackle. We propose a two-step approach consisting of line detection and subsequent tracking. The automatic detection of the lines avoids manual initialization - a typical problem of these scenarios - and favors tracking. The additional information provided by the line detection enables the improvement of existing algorithms and extends their application to a larger set of scenarios.

Abstract

Abstract
Automatic image registration is still an actual challenge in several fields. Although several methods for automatic image registration have been proposed in the last few years, it is still far from a broad use in several applications, such as in remote sensing. In this paper, a method for automatic image registration through histogram-based image segmentation (HAIRIS) is proposed. This new approach mainly consists in combining several segmentations of the pair of images to be registered, according to a relaxation parameter on the histogram modes delineation (which itself is a new approach), followed by a consistent characterization of the extracted objects-through the objects area, ratio between the axis of the adjust ellipse, perimeter and fractal dimension-and a robust statistical based procedure for objects matching. The application of the proposed methodology is illustrated to simulated rotation and translation. The first dataset consists in a photograph and a rotated and shifted version of the same photograph, with different levels of added noise. It was also applied to a pair of satellite images with different spectral content and simulated translation, and to real remote sensing examples comprising different viewing angles, different acquisition dates and different sensors. An accuracy below 1 for rotation and at the subpixel level for translation were obtained, for the most part of the considered situations. HAIRIS allows for the registration of pairs of images (multitemporal and multisensor) with differences in rotation and translation, with small differences in the spectral content, leading to a subpixel accuracy.

Abstract
Automatic image registration (AIR) is still a present challenge for the remote sensing community. Although a wide variety of AIR methods have been proposed in the last few years, there are several drawbacks which avoid their common use in practice. The recently proposed scale invariant feature transform (SIFT) approach has already revealed to be a powerful tool for the obtention of tie points in general image processing tasks, but it has a limited performance when directly applied to remote sensing images. In this paper, a new AIR method is proposed, based on the combination of image segmentation and SIFT, complemented by a robust procedure of outlier removal. This combination allows for an accurate obtention of tie points for a pair of remote sensing images, being a powerful scheme for AIR. Both synthetic and real data have been considered in this work for the evaluation of the proposed methodology, comprising medium and high spatial resolution images, and single-band, multispectral, and hyperspectral images. A set of measures which allow for an objective evaluation of the geometric correction process quality has been used. The proposed methodology allows for a fully automatic registration of pairs of remote sensing images, leading to a subpixel accuracy for the whole considered data set. Furthermore, it is able to account for differences in spectral content, rotation, scale, translation, different viewpoint, and change in illumination.