scholarly journals A FAST APPROACH FOR THE LOG-CUMULANTS METHOD APPLIED TO INTENSITY SAR IMAGE PROCESSING

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 499-503
Author(s):  
F. A. A. Rodrigues ◽  
J. S. Nobre ◽  
R. Vigélis ◽  
V. Liesenberg ◽  
R. C. P. Marques ◽  
...  
Keyword(s):  
Image Processing ◽  
Parameter Estimation ◽  
Change Detection ◽  
Single Channel ◽  
Computational Cost ◽  
Estimation Method ◽  
Computational Time ◽  
Sar Image ◽  
Fast Approach ◽  
Sar Data

Abstract. Synthetic aperture radar (SAR) image processing and analysis rely on statistical modeling and parameter estimation of the probability density functions that characterize data. The method of log-cumulants (MoLC) is a reliable alternative for parameter estimation of SAR data models and image processing. However, numerical methods are usually applied to estimate parameters using MoLC, and it may lead to a high computational cost. Thus, MoLC may be unsuitable for real-time SAR imagery applications such as change detection and marine search and rescue, for example. Our paper introduces a fast approach to overcome this limitation of MoLC, focusing on parameter estimation of single-channel SAR data modeled by the G0I distribution. Experiments with simulated and real SAR data demonstrate that our approach performs faster than MoLC, while the precision of the estimation is comparable with that of the original MoLC. We tested the fast approach with multitemporal data and applied the arithmetic-geometric distance to real SAR images for change detection on the ocean. The experiments showed that the fast MoLC outperformed the original estimation method with regard to the computational time.

Parameter Estimation and Restoration of Motion-Blurred Images

2012 ◽  
Vol 239-240 ◽  
pp. 1138-1141
Author(s):  
Pei Zhi Wen ◽  
Kai Guo ◽  
Li Fang Li
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Parameter Estimation ◽  
Image Restoration ◽  
Estimation Method ◽  
Parameter Estimation Method ◽  
Length Estimation ◽  
Blurred Image ◽  
Blurred Images

The motion-blurred image restoration has been the difficulty of the field of image processing. In this paper, proposed a motion-blurred length method based on Fourier transform of the parameter estimation method. The method improved the accuracy of the blurred length estimation. The method improved the effect of the motion-blurred image restoration. The experiments verified that the accuracy and feasibility of the method proposed.

Parameter Estimation of Generalized Gamma Distribution Toward SAR Image Processing

2020 ◽  
Vol 56 (5) ◽  
pp. 3701-3717
Author(s):  
Peng Zhang ◽  
Beibei Li ◽  
Mohamed El Yazid Boudaren ◽  
Junkun Yan ◽  
Ming Li ◽  
...  
Keyword(s):  
Image Processing ◽  
Parameter Estimation ◽  
Gamma Distribution ◽  
Sar Image ◽  
Generalized Gamma Distribution ◽  
Generalized Gamma

Markov models for ion channels: versatility versus identifiability and speed

2009 ◽  
Vol 367 (1896) ◽  
pp. 2161-2179 ◽  
Author(s):  
Martin Fink ◽  
Denis Noble
Keyword(s):  
Parameter Estimation ◽  
Cardiac Electrophysiology ◽  
Markov Models ◽  
Single Channel ◽  
Model Development ◽  
Computational Cost ◽  
Computation Time ◽  
State Variables ◽  
Gating Currents ◽  
State Dependent

Markov models (MMs) represent a generalization of Hodgkin–Huxley models. They provide a versatile structure for modelling single channel data, gating currents, state-dependent drug interaction data, exchanger and pump dynamics, etc. This paper uses examples from cardiac electrophysiology to discuss aspects related to parameter estimation. (i) Parameter unidentifiability (found in 9 out of 13 of the considered models) results in an inability to determine the correct layout of a model, contradicting the idea that model structure and parameters provide insights into underlying molecular processes. (ii) The information content of experimental voltage step clamp data is discussed, and a short but sufficient protocol for parameter estimation is presented. (iii) MMs have been associated with high computational cost (owing to their large number of state variables), presenting an obstacle for multicellular whole organ simulations as well as parameter estimation. It is shown that the stiffness of models increases computation time more than the number of states. (iv) Algorithms and software programs are provided for steady-state analysis, analytical solutions for voltage steps and numerical derivation of parameter identifiability. The results provide a new standard for ion channel modelling to further the automation of model development, the validation process and the predictive power of these models.

A Parameter Estimation Method for Poly-Phase Coded Signal Based on the Modified Fractional Fourier Transform

2012 ◽  
Vol 588-589 ◽  
pp. 715-718
Author(s):  
Guo Yi Zhang ◽  
Xu Zhou Zhang ◽  
Jia Na Li
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Signal To Noise Ratio ◽  
Computational Cost ◽  
Estimation Method ◽  
Wigner Transform ◽  
Signal To Noise ◽  
Quadratic Phase ◽  
Estimate Frequency

To estimate parameters of poly-phase coded radar signals, a modified Fractional Fourier transform (FrFT) is advanced. This algorithm employs Integrated Quadratic Phase function (IQPF) to estimate frequency rate with which the best degree for Frft is computed. Its computational cost is lower than that of Radon-Wigner transform (RWT) and Radon-Ambiguity transform (RAT). When the signal-to-noise ratio (SNR) is -7 dB, Simulations show its parameter estimation performance closes to the Cramer-Rao Lower Bounds (CRLB).

scholarly journals Synthetic Aperture Radar Image Background Clutter Fitting Using SKS + MoM-BasedG0Distribution

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Zhengwei Zhu ◽  
Jianjiang Zhou ◽  
Hongyu Chu
Keyword(s):  
Parameter Estimation ◽  
Synthetic Aperture Radar ◽  
Estimation Method ◽  
Synthetic Aperture Radar Image ◽  
Synthetic Aperture ◽  
Characteristic Functions ◽  
Sar Image ◽  
Method Of Moment ◽  
Distribution Parameter Estimation ◽  
Aperture Radar

G0distribution can accurately model various background clutters in the single-look and multilook synthetic aperture radar (SAR) images and is one of the most important statistic models in the field of SAR image clutter modeling. However, the parameter estimation ofG0distribution is difficult, which greatly limits the application of the distribution. In order to solve the problem, a fast and accurateG0distribution parameter estimation method, which combines second-kind statistics (SKS) technique with Freitas’ method of moment (MoM), is proposed. First we deduce the first and second second-kind characteristic functions ofG0distribution based on Mellin transform, and then the logarithm moments and the logarithm cumulants corresponding to the above-mentioned characteristic functions are derived; finally combined with Freitas’ method of moment, a simple iterative equation which is used for estimating theG0distribution parameters is obtained. Experimental results show that the proposed method has fast estimation speed and high fitting precision for various measured SAR image clutters with different resolutions and different number of looks.

A Fast Approach for the Log-Cumulants Method Applied to Intensity Sar Image Processing

2020 ◽  
Author(s):  
F. A. A. Rodrigues ◽  
J. S. Nobre ◽  
R. Vigaelis ◽  
V. Liesenberg ◽  
R. C. P. Marques ◽  
...  
Keyword(s):  
Image Processing ◽  
Sar Image ◽  
Fast Approach

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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