An empirical study of machine learning techniques applied to image watermarking

A study of how the machine learning technique, known as gentleboost, could improve different digital watermarking methods such as LSB, DWT, DCT2 and Histogram shifting.

Positioning an underwater vehicle through image mosaicking

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle

An analysis of visual adaptation and contrast perception for tone mapping

Tone Mapping is the problem of compressing the range of a High-Dynamic Range image so that it can be displayed in a Low-Dynamic Range screen, without losing or introducing novel details: The final image should produce in the observer a sensation as close as possible to the perception produced by the real-world scene. We propose a tone mapping operator with two stages. The first stage is a global method that implements visual adaptation, based on experiments on human perception, in particular we point out the importance of cone saturation. The second stage performs local contrast enhancement, based on a variational model inspired by color vision phenomenology. We evaluate this method with a metric validated by psychophysical experiments and, in terms of this metric, our method compares very well with the state of the art.

A Classification of Adjectives for Polarity Lexicons Enhancement

Subjective language detection is one of the most important challenges in Sentiment Analysis. Because of the weight and frequency in opinionated texts, adjectives are considered a key piece in the opinion extraction process. These subjective units are more and more frequently collected in polarity lexicons in which they appear annotated with their prior polarity. However, at the moment, any polarity lexicon takes into account prior polarity variations across domains. This paper proves that a majority of adjectives change their prior polarity value depending on the domain. We propose a distinction between domain dependent and romain independent adjectives. Moreover, our analysis led us to propose a further classification related to subjectivity degree: constant, mixed and highly subjective adjectives. Following this classification, polarity values will be a better support for Sentiment Analysis.

Putting health in all policies: The National Institute for Welfare Enhancement

Welfare is a rather vague term whose meaning depends on ideology, values andjudgments. Material resources are just means to enhance people s well-being, butgrowth of the Gross Domestic Production is still the standard measure of thesuccess of a society. Fortunately, recent advances in measuring social performanceinclude health, education and other social outcomes. Because what we measureaffects what we do it is hoped that social policies will change. The movementHealth in all policies and its associated Health Impact Assessment methodologywill contribute to it. The task consists of designing transversal policies thatconsider health and other welfare goals, the short term and long-term implicationsand intergenerational redistributions of resources. As long as marginalproductivity on health outside the healthcare system is higher than inside it,efficiency needs cross-sectoral policies. And fairness needs them even more,because in order to reduce social inequalities in health, a wide social and politicalresponse is needed.Unless we reduce the well-documented inefficiencies in our current health caresystems the welfare states will fail to consolidate and the overall economic wellbeingcould be in serious trouble. In this article we sketched some policy solutionssuch as pricing according to net benefits of innovation and public encouragementof radical innovation besides the small type incremental and market-ledinnovation. We proposed an independent agency, the National Institute forWelfare Enhancement to guarantee long term fair and efficient social policies inwhich health plays a central role.

Parallelizing remote sensing image geometric correction

Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.

Multiresolution-based image fusion with additive wavelet decomposition

The standard data fusion methods may not be satisfactory to merge a high-resolution panchromatic image and a low-resolution multispectral image because they can distort the spectral characteristics of the multispectral data. The authors developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of such images. The method presented consists of adding the wavelet coefficients of the high-resolution image to the multispectral (low-resolution) data. They have studied several possibilities concluding that the method which produces the best results consists in adding the high order coefficients of the wavelet transform of the panchromatic image to the intensity component (defined as L=(R+G+B)/3) of the multispectral image. The method is, thus, an improvement on standard intensity-hue-saturation (IHS or LHS) mergers. They used the ¿a trous¿ algorithm which allows the use of a dyadic wavelet to merge nondyadic data in a simple and efficient scheme. They used the method to merge SPOT and LANDSATTM images. The technique presented is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.

Image restoration in astronomy: a Bayesian perspective

When preparing an article on image restoration in astronomy, it is obvious that some topics have to be dropped to keep the work at reasonable length. We have decided to concentrate on image and noise models and on the algorithms to find the restoration. Topics like parameter estimation and stopping rules are also commented on. We start by describing the Bayesian paradigm and then proceed to study the noise and blur models used by the astronomical community. Then the prior models used to restore astronomical images are examined. We describe the algorithms used to find the restoration for the most common combinations of degradation and image models. Then we comment on important issues such as acceleration of algorithms, stopping rules, and parameter estimation. We also comment on the huge amount of information available to, and made available by, the astronomical community.

Introduction of sensor spectral response into image fusion methods. Application to wavelet-based methods

Usual image fusion methods inject features from a high spatial resolution panchromatic sensor into every low spatial resolution multispectral band trying to preserve spectral signatures and improve spatial resolution to that of the panchromatic sensor. The objective is to obtain the image that would be observed by a sensor with the same spectral response (i.e., spectral sensitivity and quantum efficiency) as the multispectral sensors and the spatial resolution of the panchromatic sensor. But in these methods, features from electromagnetic spectrum regions not covered by multispectral sensors are injected into them, and physical spectral responses of the sensors are not considered during this process. This produces some undesirable effects, such as resolution overinjection images and slightly modified spectral signatures in some features. The authors present a technique which takes into account the physical electromagnetic spectrum responses of sensors during the fusion process, which produces images closer to the image obtained by the ideal sensor than those obtained by usual wavelet-based image fusion methods. This technique is used to define a new wavelet-based image fusion method.

Enhancement of the photoelectrochemical properties of Cl-doped ZnO nanowires by tuning their coaxial doping profile

Arrays of vertically aligned ZnO:Cl/ZnO core-shell nanowires were used to demonstrate that the control of the coaxial doping profile in homojunction nanostructures can improve their surface charge carrier transfer while conserving potentially excellent transport properties. It is experimentally shown that the presence of a ZnO shell enhances the photoelectrochemical properties of ZnO:Cl nanowires up to a factor 5. Likewise, the ZnO shell promotes the visible photoluminescence band in highly conducting ZnO:Cl nanowires. These lines of evidence are associated with the increase of the nanowires" surface depletion layer

Side scan sonar image and geologic interpretation of the Ria de Pontevedra seafloor (Galicia, NW Spain).

High-resolution side scan sonar has been used for mapping the seafloor of the Ría de Pontevedra. Four backscatter patterns have been mapped within the Ría: (1) Pattern with isolated reflections, correlated with granite and metamorphic outcrops and located close to the coastal prominence and Ons and Onza Islands. (2) Pattern of strong reflectivity usually located around the basement outcrops and near the coastline and produced by coarse-grained sediment. (3) Pattern of weak backscatter is correlated with fine sand to mud and comprising large areas in the central and deep part of the Ría, where the bottom currents are weak. It is generally featureless, except where pockmarks and anthropogenic features are present. (4) Patches of strong and weak backscatter are located in the boundary between coarse and fine-grained sediments and they are due to the effect of strong bottom currents. The presence of megaripples associated to both patterns of strong reflectivity and sedimentary patches indicate bedload transport of sediment during high energy conditions (storms). Side scan sonar records and supplementary bathymetry, bottom samples and hydrodynamic data reveal that the distribution of seafloor sediment is strongly related to oceanographic processes and the particular morphology and topography of the Ría.

Comment on the plasmon model for image-potential-induced surface states

Calculations of the binding energy of bound positron states in metal surfaces, with explicit inclusion of plasmon dispersion and single-particle effects, are presented. The binding energy is greatly reduced with respect to the undispersed case.

Semiclassical image potential at a solid surface

A surface dielectric function of a semi-infinite plane-bounded metal is defined in the spirit of the plasmon-pole dielectric function of the bulk. It is modeled in such a way that the surface-plasmon dispersion relation is recovered for small momentum transfer. This function is employed to compute the image potential at all distances outside the surface. Interaction with bulk modes is neglected for simplicity and clarity. The interaction of a massive point charge with a metal surface is also considered in the context of a boson model for surface-plasmon excitation. We present a new definition of the image potential for this case.

Generic finite-size enhancement of pairing in mesoscopic Fermi systems

The finite-size-dependent enhancement of pairing in mesoscopic Fermi systems is studied under the assumption that the BCS approach is valid and that the two-body force is size independent. Different systems are investigated such as superconducting metallic grains and films as well as atomic nuclei. It is shown that the finite size enhancement of pairing in these systems is in part due to the presence of a surface which accounts quite well for the data of nuclei and explains a good fraction of the enhancement in Al grains.