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A novel model for three-dimensional imaging using interferometric ISAR in any curved target flight path
, Article IEEE Transactions on Geoscience and Remote Sensing ; Vol. 52, issue. 6 , 2014 , pp. 3236-3245 ; ISSN: 01962892 ; Bastani, M. H ; Sharif University of Technology
Abstract
Using a second receiver antenna close to the main transceiver antenna of inverse synthetic aperture radar (ISAR), it is possible to find 3-D positions of target scattering points. Such system is called bistatic, monopulse, or interferometric ISAR (InISAR). In the conventional model of ISAR, the unknown flying object should have a linear trajectory, and only small deviations from this trajectory can be compensated. Target motions which are highly nonlinear or curvy cannot be used in the conventional model. In this paper, we propose a new model for InISAR to process all collected data from the target, regardless of the form of the flight path. More accuracy is achieved for 3-D positioning of...
Pattern analysis by active learning method classifier
, Article Journal of Intelligent and Fuzzy Systems ; Vol. 26, issue. 1 , 2014 , p. 49-62 ; Shouraki, S. B ; Afrakoti, I. E. P ; Sharif University of Technology
Abstract
Active Learning Method (ALM) is a powerful fuzzy soft computing tool, developed originally in order to promote an engineering realization of human brain. This algorithm, as a macro-level brain imitation, has been inspired by some behavioral specifications of human brain and active learning ability. ALM is an adaptive recursive fuzzy learning algorithm, in which a complex Multi Input, Multi Output system can be represented as a fuzzy combination of several Single-Input, Single-Output systems. SISO systems as associative layer of algorithm capture partial spatial knowledge of sample data space, and enable a granular knowledge resolution tuning mechanism through the learning process. The...
Lattice Boltzmann method on quadtree grids for simulating fluid flow through porous media: A new automatic algorithm
, Article Physica A: Statistical Mechanics and its Applications ; Volume 392, Issue 20 , 2013 , Pages 4772-4786 ; 03784371 (ISSN) ; Jamshidi, S ; Masihi, M ; Sharif University of Technology
2013
Abstract
During the past two decades, the lattice Boltzmann (LB) method has been introduced as a class of computational fluid dynamic methods for fluid flow simulations. In this method, instead of solving the Navier Stocks equation, the Boltzmann equation is solved to simulate the flow of a fluid. This method was originally developed based on uniform grids. However, in order to model complex geometries such as porous media, it can be very slow in comparison with other techniques such as finite differences and finite elements. To eliminate this limitation, a number of studies have aimed to formulate the lattice Boltzmann on the unstructured grids. This paper deals with simulating fluid flow through a...
MRI image reconstruction via new K-space sampling scheme based on separable transform
, Article Iranian Conference on Machine Vision and Image Processing, MVIP ; September , 2013 , Pages 127-130 ; 21666776 (ISSN) ; 9781467361842 (ISBN) ; Ghaffari, A ; Fatemizadeh, E ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
Reducing the time required for MRI, has taken a lot of attention since its inventions. Compressed sensing (CS) is a relatively new method used a lot to reduce the required time. Usage of ordinary compressed sensing in MRI imaging needs conversion of 2D MRI signal (image) to 1D signal by some techniques. This conversion of the signal from 2D to 1D results in heavy computational burden. In this paper, based on separable transforms, a method is proposed which enables the usage of CS in MRI directly in 2D case. By means of this method, imaging can be done faster and with less computational burden
Compressed sensing and multiple image fusion: An information theoretic approach
, Article Iranian Conference on Machine Vision and Image Processing, MVIP ; 2013 , Pages 339-342 ; 21666776 (ISSN) ; 9781467361842 (ISBN) ; Mashhadi, S ; Engineers (IEEE) Antennas and Propagation Society; The Institute of Electrical and Electronics ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
In this paper, we propose an information theoretic approach to fuse images compressed by compressed sensing (CS) techniques. The goal is to fuse multiple compressed images directly using measurements and reconstruct the final image only once. Since the reconstruction is the most expensive step, it would be a more economic method than separate reconstruction of each image. The proposed scheme is based on calculating the result using weighted average on the measurements of the inputs, where weights are calculated by information theoretic functions. The simulation results show that the final images produced by our method have higher quality than those produced by traditional methods, especially...
Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation
, Article Magnetic Resonance Imaging ; Volume 31, Issue 5 , 2013 , Pages 733-741 ; 0730725X (ISSN) ; Fatemizadeh, E ; Behnam, H ; Sharif University of Technology
2013
Abstract
Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods...
Adaptive sparse representation for MRI noise removal
, Article Biomedical Engineering - Applications, Basis and Communications ; Volume 24, Issue 5 , October , 2012 , Pages 383-394 ; 10162372 (ISSN) ; Fatemizadeh, E ; Behnam, H ; Sharif University of Technology
World Scientific
2012
Abstract
Sparse representation is a powerful tool for image processing, including noise removal. It is an effective method for Gaussian noise removal by taking advantage of a fixed and learned dictionary. In this study, the variable distribution of Rician noise is reduced in magnetic resonance (MR) images by sparse representation based on reconstruction error sets. Standard deviation of Gaussian noise is used to find these errors locally. The proposed method represents two formulas for local error calculation using standard deviation of noise. The acquired results from the real and simulated images are comparable, and in some cases, better than the best Rician noise removal method due to the...
Practical design of low-cost instrumentation for industrial electrical impedance tomography (EIT)
, Article ; 2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings, 13 May 2012 through 16 May 2012, Graz , 2012 , Pages 1259-1263 ; 9781457717710 (ISBN) ; Vosoughi Vahdat, B ; Mortazavi, M ; Hy, W ; Soleimani, M ; Sharif University of Technology
IEEE
2012
Abstract
Electrical Impedance Tomography (EIT), is one of the medical imaging technologies. It can also be used in industrial process monitoring. In this method, the image of the electrical conductivity distribution of the inner part of a conductive subject can be reconstructed. The image reconstruction process is done by injecting an accurate current into the boundary of a conductive subject (e.g. body), measuring the voltages around the boundary and transmitting them to a computer, and processing on acquired data with a software (e.g., MATLAB). The images are obtained from the peripheral data by using an algorithm. Precise EIT instrumentation plays an important role in the final images quality. In...
A two-step watermarking attack using long-range correlation image restoration
, Article Security and Communication Networks ; Volume 5, Issue 6 , AUG , 2012 , Pages 625-635 ; 19390122 (ISSN) ; Jamzad, M ; Sharif University of Technology
2012
Abstract
This paper presents an efficient scheme for blind watermark attacking using the concept of matching of the long-range data. The main idea of the proposed attack is to add plenty of noise to the watermarked image and then try to restore an unwatermarked copy of the noisy image. The aim is to destroy the watermark information without accessing the parameters used during the watermark embedding process. So, it allows our approach to be completely free from any pre-assumption on the watermarking algorithm or any other parameters that is used during the watermark embedding procedure. Experimental results show the proposed algorithm's superiority over several other traditional watermarking...
Reconstruction of tomographic medical images using Kalman filter approach
, Article Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011, 18 July 2011 through 21 July 2011 ; Volume 1 , July , 2011 , Pages 236-240 ; 9781601321916 (ISBN) ; Ghorshi, S ; Mortazavi, M ; Sharif University of Technology
2011
Abstract
Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Image reconstruction is essential for medical images for some applications such as suppression of noise or de-blurring the image to provide images with better quality and contrast. In this paper Kalman filter technique is introduced for medical image reconstruction. This technique is operated in time domain unlike the filtered back projection which operates in frequency domain. Results indicated that as the number of projection increases in both the collected ray sum corrupted by noise and by blurring the quality of reconstructed image...
Simple and efficient remote sensing image transformation for lossless compression
, Article Proceedings of SPIE - The International Society for Optical Engineering ; Volume 8285 , 2011 ; 0277786X (ISSN) ; 9780819489326 (ISBN) ; Ghamisi, P ; Mortazavi, M ; Choupan, J ; Sharif University of Technology
2011
Abstract
Remote Sensing (RS) images or satellite images include information about earth. Compression of RS images is important in the field of satellite transmission systems and mass storage purposes. Because of importance of information and existent of large amount of details, lossless compression preferred. Real time compression technique is applied on satellite and aerial transmission systems [1]. A simple algorithm accelerates the whole process in real time purposes. Lossless JPEG, JPEG-LS and JPEG2000 are some famous lossless compression methods. Transformation is the first step of these methods. In this paper, a simple and efficient method of lossless image transformation has been introduced by...
Tomographical medical image reconstruction using Kalman filter technique
, Article Proceedings - 9th IEEE International Symposium on Parallel and Distributed Processing with Applications Workshops, ISPAW 2011 - ICASE 2011, SGH 2011, GSDP 2011, 26 May 2011 through 28 May 2011 ; May , 2011 , Pages 61-65 ; 9780769544298 (ISBN) ; Ghorshi, S ; Sharif University of Technology
2011
Abstract
In this paper, a Kalman filter technique which is operated in time is introduced for noise reduction on CT set of projections to reconstruct medical images. The experiments were done on medical image of kidneys and the simulated projections are captured by CT scanner. Evaluation results indicated that as the number of projections increase in the collected ray sums corrupted by noise the quality of reconstructed image becomes better in terms of contrast and transparency. However, for the comparison issue, the same conditions are applied for reconstruction of medical image in frequency domain using filter back projection technique. It observes that filter back projection technique does not...
Two-dimensional random projection
, Article Signal Processing ; Volume 91, Issue 7 , 2011 , Pages 1589-1603 ; 01651684 (ISSN) ; Babaie-Zadeh, M ; Abrishami Moghaddam, H ; Sharif University of Technology
2011
Abstract
As an alternative to adaptive nonlinear schemes for dimensionality reduction, linear random projection has recently proved to be a reliable means for high-dimensional data processing. Widespread application of conventional random projection in the context of image analysis is, however, mainly impeded by excessive computational and memory requirements. In this paper, a two-dimensional random projection scheme is considered as a remedy to this problem, and the associated key notion of concentration of measure is closely studied. It is then applied in the contexts of image classification and sparse image reconstruction. Finally, theoretical results are validated within a comprehensive set of...
A Kalman filter technique applied for medical image reconstruction
, Article International Multi-Conference on Systems, Signals and Devices, SSD'11 - Summary Proceedings, 22 March 2011 through 25 March 2011, Sousse ; 2011 ; 9781457704130 (ISBN) ; Ghorshi, S ; Manzuri, M. T ; Mortazavi, M ; Sharif University of Technology
2011
Abstract
Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as filtered back projection. In this paper, a Kalman filter technique which is operated in time domain is introduced for reconstruction of CT medical images. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of...
Image restoration using gaussian mixture models with spatially constrained patch clustering
, Article IEEE Transactions on Image Processing ; Volume 24, Issue 11 , June , 2015 , Pages 3624-3636 ; 10577149 (ISSN) ; Rabbani, H ; Babaie Zadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
In this paper, we address the problem of recovering degraded images using multivariate Gaussian mixture model (GMM) as a prior. The GMM framework in our method for image restoration is based on the assumption that the accumulation of similar patches in a neighborhood are derived from a multivariate Gaussian probability distribution with a specific covariance and mean. Previous methods of image restoration with GMM have not considered spatial (geometric) distance between patches in clustering. Our conducted experiments show that in the case of constraining Gaussian estimates into a finite-sized windows, the patch clusters are more likely to be derived from the estimated multivariate Gaussian...
Microwave medical imaging based on sparsity and an iterative method with adaptive thresholding
, Article IEEE Transactions on Medical Imaging ; Volume 34, Issue 2 , September , 2015 , Pages 357-365 ; 02780062 (ISSN) ; Kosmas, P ; Marvasti, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
We propose a new image recovery method to improve the resolution in microwave imaging applications. Scattered field data obtained from a simplified breast model with closely located targets is used to formulate an electromagnetic inverse scattering problem, which is then solved using the Distorted Born Iterative Method (DBIM). At each iteration of the DBIM method, an underdetermined set of linear equations is solved using our proposed sparse recovery algorithm, IMATCS. Our results demonstrate the ability of the proposed method to recover small targets in cases where traditional DBIM approaches fail. Furthermore, in order to regularize the sparse recovery algorithm, we propose a novel...
A non-iterative linear inverse solution for the block approach in EIT
, Article Journal of Computational Science ; Volume 1, Issue 4 , 2010 , Pages 190-196 ; 18777503 (ISSN) ; Vahdat, B. V ; Sharif University of Technology
2010
Abstract
Electrical impedance tomography (EIT) is a simple, economic and healthy technique to capture images from the internal area of the body. Although EIT is cheaper and smaller than other imaging systems and requires no ionizing radiation, the resolution associated with this technique is intrinsically limited and the image reconstruction algorithms proposed up to now are not efficient enough. In addition to low resolution EIT is an ill-posed inverse problem. Block method in EIT is based on electrical properties of materials and used to enhance image resolution and also to improve the reconstruction algorithm. Recently an inverse solution for EIT based on block method has been developed, however,...
Structure and texture image inpainting
, Article Proceedings of the 2010 International Conference on Signal and Image Processing, ICSIP 2010, 15 December 2010 through 17 December 2010 ; 2010 , Pages 119-124 ; 9781424485949 (ISBN) ; Jamzad, M ; Mahdavi Amiri, N ; Sharif University of Technology
Abstract
Inpainting refers to the task of filling in the missing or damaged regions of an image in an undetectable manner. We have an image to be reconstructed in a user-defined region. We use a fast decomposition method to obtain two components of the image, namely structure and texture. Reconstruction of each component is performed separately. The missing information in the structure component is reconstructed using a structure inpainting algorithm, while the texture component is repaired by a texture synthesis technique. To obtain the inpainted image, the two reconstructed components are composed together. Taking advantage of both the structure inpainting methods and texture synthesis techniques,...
Dimension reduction of remote sensing images by incorporating spatial and spectral properties
, Article AEU - International Journal of Electronics and Communications ; Volume 64, Issue 8 , 2010 , Pages 729-732 ; 14348411 (ISSN) ; Kasaei, S ; Sharif University of Technology
Abstract
A new and efficient dimension reduction method is introduced in this paper. The proposed method, almost the same as the well-known principal component analysis (PCA) method, enjoys the properties of uncorrelatedness of resulting components and orthogonality of transform coefficients. In addition, by incorporating spatial and spectral properties among image pixels, the method obtains more accurate classification results with less computational cost
A fast 3D hand model reconstruction by stereo vision system
, Article 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010, 26 February 2010 through 28 February 2010, Singapore ; Volume 5 , 2010 , Pages 545-549 ; 9781424455850 (ISBN) ; Jahed, M ; Sharif University of Technology
2010
Abstract
The use of human hand gestures as a natural interface tool has motivated researchers to conduct research in the modeling, analyzing and recognition of various hand movements. In particular, human computer intelligent interaction has been a focus for research in vision-based gesture recognition. In this work, we introduce a 3D hand model reconstruction method which offers flexible and elaborate representation of hand gestures. We used 20 landmarked points on tips and joints of the fingers and calculated the 3D coordinates of these points through a stereo vision system. Our results show that such reconstruction provides a precise 3D hand model only to be influenced by intrinsic and extrinsic...