Sharif Digital Repository

In this paper we propose a new method to recover images corrupted with salt and pepper noise. The proposed method uses ordered statistics filtering and soft-decisioning in successive approximations to find the locations and amplitudes of all the impulses. In our method we use soft-decision to generate a mask which is based on histogram distributions in local windows to distinguish impulsive noise from legitimate pixels. This mask is used to obtain an estimate of the original image by an iterative method. The result of the aforementioned algorithm can be fed back into the system to improve the image reconstruction process. This algorithm is analyzed and verified by simulation results.... 

Particulate matter (PM) pollution is a growing concern in urban areas in the developing countries because of its potential to aggravate cardiovascular and respiratory illnesses. Traditional approaches in monitoring urban pollutants have relied on ground-based networks even though they essentially provide point measurements and are inadequate for health alerts on large spatial and long temporal scales. Recent advances in satellite imagery has attracted managers to look into this new alternative as a predictive tool for improving air quality at urban and regional scales by providing necessary data in advance of the onset of actual severe conditions. Moderate Resolution Imaging... 

A state-of-the-art algorithm for perspective projection reconstruction of non-rigid surfaces from single-view and realistic videos is proposed. It overcomes the limitations arising from the usage of orthographic camera model and also the complexity and non-linearity issues of perspective projection equation. Unlike traditional non-rigid structure-from-motion (NRSfM) methods, which have been studied only on synthetic datasets and controlled lab environments that require some prior constraints (such as manually segmented objects, limited rotations and occlusions, and full-length trajectories); the proposed method can be used in realistic video sequences. In addition, contrary to previous... 

In this paper, the relationship between the position of ultrasound transducers from the photoacoustic source and the reconstructed image is investigated. Our studies have shown that the distance of the transducer and its location from the photoacoustic source specifically affects and is closely related to the quality of the reconstructed image of the source. Also, we introduce a concept called blind angle for photoacoustic computed tomography (PACT) that have planar or circular limited-view geometry. Complete and accurate equations of this relationship are presented in this paper for all different 2D photoacoustic geometries. The main source of these equations is the spherically of the... 

Circular photoacoustic tomography (C-PAT) arrangements are widely used in PAT systems. Many algorithms are proposed for PAT to reconstruct images such as delay and sum (DAS), universal back-projection (UBP), etc., all suffering from their own disadvantages. In this paper, to overcome these limitations, we proposed a fast uniform adapted delay and sum (ADAS) and filtered adapted delay and sum (F-ADAS) for detectors with finite and infinite bandwidth, respectively. Moreover, the edge uniformity index (EUI) metric was proposed for quantitative evaluation. Two cases 1) infinite bandwidth and 25 dB SNR level and 2) 2.25 MHz, 80% bandwidth with the same SNR level were considered for numerical... 

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,... 

We propose an algorithm based on mutual information to address the problem of online reconstruction of dynamic MRI from partial k-space measurements. Most of previous compressed sensing (CS) based methods successfully leverage sparsity constraint for offline reconstruction of MR images, yet they are not used in online applications due to their complexities. In this paper, we formulate the reconstruction as a constraint optimization problem and try to maximize the mutual information between the current and the previous time frames. Conjugate gradient method is used to solve the optimization problem. Using Cartesian mask to undersample k-space measurements, the proposed method reduces... 

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... 

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... 

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... 

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... 

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...