Search results for: Fuzzy clustering algorithm

Authors: Xueting Liu, Daojin Song, Chuandai Dong, Hongkui Li

Abstract:

From a set of shifted, blurred, and decimated image , super-resolution image reconstruction can get a high-resolution image. So it has become an active research branch in the field of image restoration. In general, super-resolution image restoration is an ill-posed problem. Prior knowledge about the image can be combined to make the problem well-posed, which contributes to some regularization methods. In the regularization methods at present, however, regularization parameter was selected by experience in some cases and other techniques have too heavy computation cost for computing the parameter. In this paper, we construct a new super-resolution algorithm by transforming the solving of the System stem Є=An into the solving of the equations X+A*X-1A=I , and propose an inverse iterative method.

Keywords: High-resolution MAP image, Reconstruction, Image interpolation, Motion Estimation, Hermitian positive definite solutions.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, non-reference quality measures, objective quality measures.

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Authors: L. Petrovičová, Ž. Balážová, Z. Gálová, M. Wójcik-Jagła, M. Rapacz

Abstract:

In the present study, RAPD-PCR was used to assess genetic diversity of the rye including landrances and new rye cultivars coming from Central Europe and the Union of Soviet Socialist Republics (SUN). Five arbitrary random primers were used to determine RAPD polymorphism in the set of 38 rye genotypes. These primers amplified altogether 43 different DNA fragments with an average number of 8.6 fragments per genotypes. The number of fragments ranged from 7 (RLZ 8, RLZ 9 and RLZ 10) to 12 (RLZ 6). DI and PIC values of all RAPD markers were higher than 0.8 that generally means high level of polymorphism detected between rye genotypes. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared. The cultivars were grouped into two main clusters. In this experiment, RAPD proved to be a rapid, reliable and practicable method for revealing of polymorphism in the rye cultivars.

Keywords: Genetic diversity, polymorphism, RAPD markers, Secalecereale L.

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Authors: Carla E. O. de Moraes, Gladson O. Antunes, Mauro A. Rincon

Abstract:

The aim of this paper is to study the internal stabilization of the Bernoulli-Euler equation numerically. For this, we consider a square plate subjected to a feedback/damping force distributed only in a subdomain. An algorithm for obtaining an approximate solution to this problem was proposed and implemented. The numerical method used was the Finite Difference Method. Numerical simulations were performed and showed the behavior of the solution, confirming the theoretical results that have already been proved in the literature. In addition, we studied the validation of the numerical scheme proposed, followed by an analysis of the numerical error; and we conducted a study on the decay of the energy associated.

Keywords: Bernoulli-Euler Plate Equation, Numerical Simulations, Stability, Energy Decay, Finite Difference Method.

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Authors: Nermin Ozgulbas, Ali Serhan Koyuncugil

Abstract:

One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.

Keywords: Early Warning Systems, Data Mining, Financial Risk, SMEs.

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Authors: Jong-Whoi Shin, Chong-Sun Hwang

Abstract:

Various security APIs (Application Programming Interfaces) are being used in a variety of application areas requiring the information security function. However, these standards are not compatible, and the developer must use those APIs selectively depending on the application environment or the programming language. To resolve this problem, we propose the standard draft of the information security component, while SSL (Secure Sockets Layer) using the confidentiality and integrity component interface has been implemented to verify validity of the standard proposal. The implemented SSL uses the lower-level SSL component when establishing the RMI (Remote Method Invocation) communication between components, as if the security algorithm had been implemented by adding one more layer on the TCP/IP.

Keywords: Component Based Design, Application Programming Interface, Secure Socket Layer, Remote Method Invocation.

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Authors: Hijun Kim, Jungkeun Sung, Seungwoo Kim

Abstract:

In this paper, a Smart Home Service Robot, McBot II, which performs mess-cleanup function etc. in house, is designed much more optimally than other service robots. It is newly developed in much more practical system than McBot I which we had developed two years ago. One characteristic attribute of mobile platforms equipped with a set of dependent wheels is their omni- directionality and the ability to realize complex translational and rotational trajectories for agile navigation in door. An accurate coordination of steering angle and spinning rate of each wheel is necessary for a consistent motion. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A specialized anthropomorphic robot manipulator which can be attached to the housemaid robot McBot II, is developed in this paper. This built-in type manipulator consists of both arms with 3 DOF (Degree of Freedom) each and both hands with 3 DOF each. The robotic arm is optimally designed to satisfy both the minimum mechanical size and the maximum workspace. Minimum mass and length are required for the built-in cooperated-arms system. But that makes the workspace so small. This paper proposes optimal design method to overcome the problem by using neck joint to move the arms horizontally forward/backward and waist joint to move them vertically up/down. The robotic hand, which has two fingers and a thumb, is also optimally designed in task-based concept. Finally, the good performance of the developed McBot II is confirmed through live tests of the mess-cleanup task.

Keywords: Holonomic Omni-wheeled Mobile Robot, Special-purpose, Manipulation, Home Service Robot

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Authors: H. Dujmic, V. Papic, H. Turic

Abstract:

The article presents a new method for detection of artificial objects and materials from images of the environmental (non-urban) terrain. Our approach uses the hue and saturation (or Cb and Cr) components of the image as the input to the segmentation module that uses the mean shift method. The clusters obtained as the output of this stage have been processed by the decision-making module in order to find the regions of the image with the significant possibility of representing human. Although this method will detect various non-natural objects, it is primarily intended and optimized for detection of humans; i.e. for search and rescue purposes in non-urban terrain where, in normal circumstances, non-natural objects shouldn-t be present. Real world images are used for the evaluation of the method.

Keywords: Landscape surveillance, mean shift algorithm, image segmentation, target detection.

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Authors: Eiad Yafi, M. A. Alam, Ranjit Biswas

Abstract:

Knowledge Discovery of Databases (KDD) is the process of extracting previously unknown but useful and significant information from large massive volume of databases. Data Mining is a stage in the entire process of KDD which applies an algorithm to extract interesting patterns. Usually, such algorithms generate huge volume of patterns. These patterns have to be evaluated by using interestingness measures to reflect the user requirements. Interestingness is defined in different ways, (i) Objective measures (ii) Subjective measures. Objective measures such as support and confidence extract meaningful patterns based on the structure of the patterns, while subjective measures such as unexpectedness and novelty reflect the user perspective. In this report, we try to brief the more widely spread and successful subjective measures and propose a new subjective measure of interestingness, i.e. shocking.

Keywords: Shocking rules (SHR).

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Authors: Tudor Barbu

Abstract:

An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Then, an automatic pixel classification approach is proposed. The feature vectors are clustered using an unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: Image segmentation, moment-based texture analysis, automatic classification, validity indexes.

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Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

Abstract:

Leo Breimans Random Forests (RF) is a recent development in tree based classifiers and quickly proven to be one of the most important algorithms in the machine learning literature. It has shown robust and improved results of classifications on standard data sets. Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques to the random forests. We experiment the working of the ensembles of random forests on the standard data sets available in UCI data sets. We compare the original random forest algorithm with their ensemble counterparts and discuss the results.

Keywords: Random Forests [RF], ensembles, UCI.

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Authors: C. Rajan, N. Shanthi, C. Rasi Priya, K. Geetha

Abstract:

Routing in MANET is extremely challenging because of MANETs dynamic features, its limited bandwidth, frequent topology changes caused by node mobility and power energy consumption. In order to efficiently transmit data to destinations, the applicable routing algorithms must be implemented in mobile ad-hoc networks. Thus we can increase the efficiency of the routing by satisfying the Quality of Service (QoS) parameters by developing routing algorithms for MANETs. The algorithms that are inspired by the principles of natural biological evolution and distributed collective behavior of social colonies have shown excellence in dealing with complex optimization problems and are becoming more popular. This paper presents a survey on few meta-heuristic algorithms and naturally-inspired algorithms.

Keywords: Ant colony optimization, genetic algorithm, Naturally-inspired algorithms and particle swarm optimization.

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Authors: R. Khorshidi , T. Niknam, M. Nayeripour

Abstract:

Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. Fueling the attention have been the possibilities of international agreements to reduce greenhouse gas emissions, electricity sector restructuring, high power reliability requirements for certain activities, and concern about easing transmission and distribution capacity bottlenecks and congestion. So it is necessary that impact of these kinds of generators on distribution feeder reconfiguration would be investigated. This paper presents an approach for distribution reconfiguration considering Distributed Generators (DGs). The objective function is summation of electrical power losses A Tabu search optimization is used to solve the optimal operation problem. The approach is tested on a real distribution feeder.

Keywords: Distributed Generator, Daily Optimal Operation, Genetic Algorithm.

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Authors: Aiswaria Ramachandran, Balaji Haiharan

Abstract:

The importance of our country-s communication system is noticeable when a disaster occurs. The communication system in our country includes wired and wireless telephone networks, radio, satellite system and more increasingly internet. Even though our communication system is most extensive and dependable, extreme conditions can put a strain on them. Interoperability between heterogeneous wireless networks can be used to provide efficient communication for emergency first response. IEEE 802.21 specifies Media Independent Handover (MIH) services to enhance the mobile user experience by optimizing handovers between heterogeneous access networks. This paper presents an algorithm to improve congestion control in MIH framework. It is analytically shown that by including time factor in network selection we can optimize congestion in the network.

Keywords: Vertical Handoff, Heterogeneous Networks, MIH

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Authors: Wen-liang Chen, Peng Wei, Yidong Bao

Abstract:

This paper presents a linear-elastic finite element method based flattening algorithm for three dimensional triangular surfaces. First, an intrinsic characteristic preserving method is used to obtain the initial developing graph, which preserves the angles and length ratios between two adjacent edges. Then, an iterative equation is established based on linear-elastic finite element method and the flattening result with an equilibrium state of internal force is obtained by solving this iterative equation. The results show that complex surfaces can be dealt with this proposed method, which is an efficient tool for the applications in computer aided design, such as mould design.

Keywords: Triangular mesh, surface flattening, finite elementmethod, linear-elastic deformation.

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Authors: M. H. Abedi, A. Jalilvand

Abstract:

The economic development benefits of wind energy may be the most tangible basis for the local and state officials’ interests. In addition to the direct salaries associated with building and operating wind projects, the wind energy industry provides indirect jobs and benefits. The optimal planning of a wind farm is one most important topic in renewable energy technology. Many methods have been implemented to optimize the cost and output benefit of wind farms, but the contribution of this paper is mentioning different types of service providers and also time of installation of wind turbines during planning horizon years. Genetic algorithm (GA) is used to optimize the problem. It is observed that an appropriate layout of wind farm can cause to minimize the different types of cost.

Keywords: Renewable energy, wind farm, optimization, planning.

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Authors: H. M. Behairy, M. S. Khorsheed

Abstract:

Among other factors that characterize satellite communication channels is their high bit error rate. We present a system for still image transmission over noisy satellite channels. The system couples image compression together with error control codes to improve the received image quality while maintaining its bandwidth requirements. The proposed system is tested using a high resolution satellite imagery simulated over the Rician fading channel. Evaluation results show improvement in overall system including image quality and bandwidth requirements compared to similar systems with different coding schemes.

Keywords: Image Transmission, Image Compression, Channel Coding, Error-Control Coding, DCT, Convolution Codes, Viterbi Algorithm, PCGC.

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Authors: Seong-Ho Song, Ki-Seob Kim, Seon-Woo Lee, Seop-Hyeong Park

Abstract:

Based on a theoretical erbium-doped fiber amplifier (EDFA) model, we have proposed an application of disturbance observer(DOB) with proportional/integral/differential(PID) controller to EDFA for minimizing gain-transient time of wavelength -division-multiplexing (WDM) multi channels in optical amplifier in channel add/drop networks. We have dramatically reduced the gain-transient time to less than 30μsec by applying DOB with PID controller to the control of amplifier gain. The proposed DOB-based gain control algorithm for EDFA was implemented as a digital control system using TI's DSP(TMS320C28346) chip and experimental results of the system verify the excellent performance of the proposed gain control methodology.

Keywords: EDFA, Disturbance observer, gain control, WDM.

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Authors: N. Veerasamy, C. J. Cheyne

Abstract:

Users of computer systems may often require the private transfer of messages/communications between parties across a network. Information warfare and the protection and dominance of information in the military context is a prime example of an application area in which the confidentiality of data needs to be maintained. The safe transportation of critical data is therefore often a vital requirement for many private communications. However, unwanted interception/sniffing of communications is also a possibility. An elementary stealthy transfer scheme is therefore proposed by the authors. This scheme makes use of encoding, splitting of a message and the use of a hashing algorithm to verify the correctness of the reconstructed message. For this proof-of-concept purpose, the authors have experimented with the random sending of encoded parts of a message and the construction thereof to demonstrate how data can stealthily be transferred across a network so as to prevent the obvious retrieval of data.

Keywords: Construction, encode, interception, stealthy.

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Authors: N. Arulanand, P. M. Ananth

Abstract:

Quality of Service (QoS) attributes as part of the service description is an important factor for service attribute. It is not easy to exactly quantify the weight of each QoS conditions since human judgments based on their preference causes vagueness. As web services selection requires optimization, evolutionary computing based on heuristics to select an optimal solution is adopted. In this work, the evolutionary computing technique Particle Swarm Optimization (PSO) is used for selecting a suitable web services based on the user’s weightage of each QoS values by optimizing the QoS weight vector and thereby finding the best weight vectors for best services that is being selected. Finally the results are compared and analyzed using static inertia weight and deterministic inertia weight of PSO.

Keywords: QoS, Optimization, Particle Swarm Optimization (PSO), weight vector, web services, web service selection.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, nonreferencequality measures, objective quality measures.

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Authors: Keuk Jong Yu, Sang Hee Kang, Sung Chang You

Abstract:

In Korea, the technology of a load fo nuclear power plant has been being developed. automatic controller which is able to control temperature and axial power distribution was developed. identification algorithm and a model predictive contact former transforms the nuclear reactor status into numerically. And the latter uses them and ge manipulated values such as two kinds of control ro this automatic controller, the performance of a coperation was evaluated. As a result, the automatic generated model parameters of a nuclear react to nuclear reactor average temperature and axial power the desired targets during a daily load follow.

Keywords: axial power distribution, model reactor temperature, system identification

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Authors: Imron Rosyadi, Ridha A. Djemal, Saleh A. Alshebeili

Abstract:

Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.

Keywords: CFAR, FPGA, radar.

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Authors: Boontee Kruatrachue, Narongchai Moongfangklang, Kritawan Siriboon

Abstract:

This paper describes fast and efficient method for page segmentation of document containing nonrectangular block. The segmentation is based on edge following algorithm using small window of 16 by 32 pixels. This segmentation is very fast since only border pixels of paragraph are used without scanning the whole page. Still, the segmentation may contain error if the space between them is smaller than the window used in edge following. Consequently, this paper reduce this error by first identify the missed segmentation point using direction information in edge following then, using X-Y cut at the missed segmentation point to separate the connected columns. The advantage of the proposed method is the fast identification of missed segmentation point. This methodology is faster with fewer overheads than other algorithms that need to access much more pixel of a document.

Keywords: Contour Direction Technique, Missed SegmentationPoints, Page Segmentation, Recursive X-Y Cut Technique

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Authors: Daxing Wang, Jikai Teng

Abstract:

An aggregate signature scheme can aggregate n signatures on n distinct messages from n distinct signers into a single signature. Thus, n verification equations can be reduced to one. So the aggregate signature adapts to Mobile Ad hoc Network (MANET). In this paper, we propose an efficient ID-based aggregate signature scheme with constant pairing computations. Compared with the existing ID-based aggregate signature scheme, this scheme greatly improves the efficiency of signature communication and verification. In addition, in this work, we apply our ID-based aggregate sig- nature to authenticated routing protocol to present a secure routing scheme. Our scheme not only provides sound authentication and a secure routing protocol in ad hoc networks, but also meets the nature of MANET.

Keywords: Identity-based cryptography, Aggregate signature, Bilinear pairings, Authenticated routing scheme.

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Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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Authors: Salem Belhaj, Moncef Tagina

Abstract:

This paper is aimed at describing a delay-based endto- end (e2e) congestion control algorithm, called Very FAST TCP (VFAST), which is an enhanced version of FAST TCP. The main idea behind this enhancement is to smoothly estimate the Round-Trip Time (RTT) based on a nonlinear filter, which eliminates throughput and queue oscillation when RTT fluctuates. In this context, an evaluation of the suggested scheme through simulation is introduced, by comparing our VFAST prototype with FAST in terms of throughput, queue behavior, fairness, stability, RTT and adaptivity to changes in network. The achieved simulation results indicate that the suggested protocol offer better performance than FAST TCP in terms of RTT estimation and throughput.

Keywords: Fast tcp, RTT, delay estimation, delay-based congestion control, high speed TCP, large bandwidth delay product.

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Authors: Soham De, Nupur Biswas, Abhijit Sanyal, Pulak Ray, Alokmay Datta

Abstract:

Particle detection in very noisy and low contrast images is an active field of research in image processing. In this article, a method is proposed for the efficient detection and sizing of subsurface spherical particles, which is used for the processing of softly fused Au nanoparticles. Transmission Electron Microscopy is used for imaging the nanoparticles, and the proposed algorithm has been tested with the two-dimensional projected TEM images obtained. Results are compared with the data obtained by transmission optical spectroscopy, as well as with conventional circular object detection algorithms.

Keywords: Transmission Electron Microscopy, Circular Hough Transform, Au Nanoparticles, Median Filter, Laplacian Sharpening Filter, Canny Edge Detection

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Authors: Oscar J.G. Somsen, Fok Bolderheij

Abstract:

Electro-optical devices are increasingly used for military sea-, land- and air applications to detect, recognize and track objects. Typically, these devices produce video information that is presented to an operator. However, with increasing availability of electro-optical devices the data volume is becoming very large, creating a rising need for automated analysis. In a military setting, this typically involves detecting and recognizing objects at a large distance, i.e. when they are difficult to distinguish from background and noise. One may consider combining multiple images from a video stream into a single enhanced image that provides more information for the operator. In this paper we investigate a simple algorithm to enhance simulated images from a military context and investigate how the enhancement is affected by various types of disturbance.

Keywords: Electro-Optics, Automated Image alignment

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Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak, Athar Mohsin, UmarFarooq

Abstract:

This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely directional smoothing filter which is an additional step. Proposed method does not need any noise estimation and thresholding technique. More over proposed method gives good results on both single polarimetric and fully polarimetric SAR images.

Keywords: Directional Smoothing, Inner product, Length ofvector, Undecimated wavelet transformation.

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