Dimensionality Reduction and Classification feature using Mutual Information applied to Hyperspectral Images : A Filter strategy based algorithm

Hyperspectral images (HIS) classification is a high technical remote sensing tool. The goal is to reproduce a thematic map that will be compared with a reference ground truth map (GT), constructed by expecting the region. The HIS contains more than a hundred bidirectional measures, called bands (or simply images), of the same region. They are taken at juxtaposed frequencies. Unfortunately, some bands contain redundant information, others are affected by the noise, and the high dimensionality of features made the accuracy of classification lower. The problematic is how to find the good bands to classify the pixels of regions. Some methods use Mutual Information (MI) and threshold, to select relevant bands, without treatment of redundancy. Others control and eliminate redundancy by selecting the band top ranking the MI, and if its neighbors have sensibly the same MI with the GT, they will be considered redundant and so discarded. This is the most inconvenient of this method, because this avoids the advantage of hyperspectral images: some precious information can be discarded. In this paper we'll accept the useful redundancy. A band contains useful redundancy if it contributes to produce an estimated reference map that has higher MI with the GT.nTo control redundancy, we introduce a complementary threshold added to last value of MI. This process is a Filter strategy; it gets a better performance of classification accuracy and not expensive, but less preferment than Wrapper strategy.Comment: 11 pages, 5 figures, journal pape

Improved IDMA for Multiple Access of 5G

Due to its good performance and low complexity, IDMA is believed to be an important technique for future radio access (FRA). However, its performances are highly affected by the interleaver design. In this paper we propose two contributions to improve the performance of the IDMA. First, we propose a new interleaver design, called "NLM interleaver", which improves the computational complexity, reduces the bandwidth consumption and the memory requirements of the system, provides the quasi-orthogonal spreading codes and interleavers with a high security and offers infinite sets of codes and interleavers based on only one parameter. Second, we propose a new user grouping algorithm based on the correlation function to improve the resources (Codes, Interleavers). All users are divided into several equal-size groups where each group's data transmitted at the same time, over the same frequencies and the same interleaver. The simulation results indicate that the proposed scheme can achieve better performances compared to the existing algorithms

A Reduced Reference Image Quality Measure Using Bessel K Forms Model for Tetrolet Coefficients

In this paper, we introduce a Reduced Reference Image Quality Assessment (RRIQA) measure based on the natural image statistic approach. A new adaptive transform called "Tetrolet" is applied to both reference and distorted images. To model the marginal distribution of tetrolet coefficients Bessel K Forms (BKF) density is proposed. Estimating the parameters of this distribution allows to summarize the reference image with a small amount of side information. Five distortion measures based on the BKF parameters of the original and processed image are used to predict quality scores. A comparison between these measures is presented showing a good consistency with human judgment

Impact of queue buffer size awareness on single and multi service real-time routing protocols for WSNs

Wireless Sensor Networks (WSNs) are increasingly used and will certainly be part of our everyday lives. Many routing protocols were designed with respect to WSNs capacities to allow the achievement of numerous applications. One of the not well investigated areas in WSNs is the queue management issue. The purpose of this paper is to present an analysis of the impact of queue buffer size awareness on the Quality of Service (QoS) of real-time (RT) routing protocols in WSNs. The studied protocols are SPEED and its extension Multipath Multi-speed (MMSPEED). SPEED protocol yields RT routing for only one class of traffic, by maintaining a desired packet’s progression speed (PS) across the WSN. On the other hand, MMSPEED protocol extends SPEED by offering multiple types of service to packets according to their class of traffic. The main contribution is that the routing decision is made on neighbors’ available queue buffer size at each level in addition to PS metric. Simulations have proved that the two metrics are compatible, the routing decision is efficient in case of single service protocol and multiservice one and improves two QoS domains namely timeliness and reliability

AmAMorph: Finite State Morphological Analyzer for Amazighe

This paper presents AmAMorph, a morphological analyzer for Amazighe language using a system based on the NooJ linguistic development environment. The paper begins with the development of Amazighe lexicons with large coverage formalization. The built electronic lexicons, named ‘NAmLex’, ‘VAmLex’ and ‘PAmLex’ which stand for ‘Noun Amazighe Lexicon’, ‘Verb Amazighe Lexicon’ and ‘Particles Amazighe Lexicon’, link inflectional, morphological, and syntacticsemantic information to the list of lemmas. Automated inflectional and derivational routines are applied to each lemma producing over inflected forms. To our knowledge,AmAMorph is the first morphological analyzer for Amazighe. It identifies the component morphemes of the forms using large coverage morphological grammars. Along with the description of how the analyzer is implemented, this paper gives an evaluation of the analyzer