Threshold Value Estimation Research Articles

An ArmurMimus multimodal biometric system for Khosher authentication

AbstractOne of the basic requirements of our modern day society is personal authentication. Biometric recognition should make a human‐like identity determination by identifying its physiological and/or behavioral characteristics. In comparison to traditional knowledge‐based approaches, biometric identification systems have the potential to bring benefits. However, because of the difficulties in extracting non‐class discriminative features, the lack of protection during storage of extracted features, and poor recognition accuracy, most frequently used biometric systems lack model protection and robustness. This research proposed a Mimus multimodal biometric system focused on the combination of multiple modalities and optimal level fusion of features to resolve these problems. Initially, the novel Blob‐funk method extracts the complementary non‐class discriminatory information among different modalities, which accomplishes the biometric data enrollment. Thus, it extracts the different properties by comparing surrounding regions based on finding the local maxima and minima of the function. After extracting the features, they need to be stored in a secure manner in a database. Therefore, the paper incorporates the new code block protection strategy to achieve an effectual protection of continuous monitoring via the generation of non‐invertible features, which is used to create the templates, thus storing them in a database. Finally, the novel Lucynomial logistic regression system incorporates user authentication and thus achieves greater recognition accuracy through estimation of threshold value with confrontation of spoof attacks. Hence, compared to the existing techniques such as SVM, PCA, and DBN, the outcome of the proposed work attains 97.53% accuracy, 0.020% FAR, 96.44% recall, and 97.85% precision, thus exemplifying the competence of the novel system.

Applying Machine Learning to Determine 25(OH)D Threshold Levels Using Data from the AMATERASU Vitamin D Supplementation Trial in Patients with Digestive Tract Cancer.

Some controversy remains on thresholds for deficiency or sufficiency of serum 25-hydroxyvitamin D (25(OH)D) levels. Moreover, 25(OH)D levels sufficient for bone health might differ from those required for cancer survival. This study aimed to explore these 25(OH)D threshold levels by applying the machine learning method of multivariable adaptive regression splines (MARS) in post hoc analyses using data from the AMATERASU trial, which randomly assigned Japanese patients with digestive tract cancer to receive vitamin D or placebo supplementation. Using MARS, threshold 25(OH)D levels were estimated as 17 ng/mL for calcium and 29 ng/mL for parathyroid hormone (PTH). Vitamin D supplementation increased calcium levels in patients with baseline 25(OH)D levels ≤17 ng/mL, suggesting deficiency for bone health, but not in those >17 ng/mL. Vitamin D supplementation improved 5-year relapse-free survival (RFS) compared with placebo in patients with intermediate 25(OH)D levels (18–28 ng/mL): vitamin D, 84% vs. placebo, 71%; hazard ratio, 0.49; 95% confidence interval, 0.25–0.96; p = 0.04. In contrast, vitamin D supplementation did not improve 5-year RFS among patients with low (≤17 ng/mL) or with high (≥29 ng/mL) 25(OH)D levels. MARS might be a reliable method with the potential to eliminate guesswork in the estimation of threshold values of biomarkers.

Microstructure based cracking behavior and life assessment of titanium alloy under very-high-cycle fatigue with elevated temperatures

High and very high cycle fatigue tests for TC11 titanium alloy were performed to clarify the interior cracking behavior under fully reversed and pulsating tension at three service temperatures. According to the estimation of threshold values for small and long crack growth, the fatigue design curves are established. Combined with electron backscatter diffraction and fracture mechanics analysis, the interior cracking is closely related to grain strength and size, and microtexture. The interior failure is attributed to the facet formation caused by larger αp phase fracture. Based on FIP model, a temperature-based method is proposed to predict the crack nucleation life.

Testing for sensory threshold in drinking water with added calcium: a first step towards developing a calcium fortified water.

Background: Food fortification is an effective strategy that has been recommended for improving population calcium inadequate intakes. Increasing calcium concentration of water has been proposed as a possible strategy to improve calcium intake. The objective of this study was to determine the sensory threshold of different calcium salts added to drinking water using survival analysis. Methods: We performed the triangle test methodology for samples of water with added calcium using three different calcium salts: calcium chloride, calcium gluconate and calcium lactate. For each salt, a panel of 54 consumers tested seven batches of three water samples. Data were adjusted for chance and sensory threshold was estimated using the survival methodology and a discrimination of 50%. Results: The threshold value estimation for calcium gluconate was 587 ± 131 mg/L of water, corresponding to 25% discrimination, for calcium lactate was 676 ± 186 mg/L, corresponding to 50% discrimination, and for calcium chloride was 291 ± 73 mg/L, corresponding to 50% discrimination. Conclusions: These results show that water with calcium added in different salts and up to a concentration of 500 mg of calcium/L of water is feasible. The calcium salt allowing the highest calcium concentration with the lowest perceived changes in taste was calcium gluconate. Future studies need to explore stability and acceptability over longer periods of time.

A fatigue life prediction approach to interior cracking induced high cycle and very high cycle fatigue for surface‐carburized steels

AbstractHigh cycle fatigue and very high cycle fatigue tests with pulsating tension for three surface‐carburized steels were performed to investigate interior failure behavior and life prediction method. As a result, all cracks with fine granular area and fisheye characteristics are induced from inclusions in matrix or in carburized layer. However, the later cracking morphology is smoother, which is due to the difference of plastic deformation and microstructure of the two regions. Based on estimation of threshold values for small and long crack growth, fatigue design curves are established. The maximum inclusion sizes of three carburizing steels were estimated by four statistical analysis methods. Combined with material microstructure characteristics and the critical plane theory, a failure‐based life prediction model is proposed by using fatigue indicator parameter, whose validity is verified based on good agreement between predicted and experimental ones.

Testing for sensory threshold in drinking water with added calcium: a first step towards developing a calcium fortified water

Background: Food fortification is an effective strategy that has been recommended for improving population calcium inadequate intakes. Increasing calcium concentration of water has been proposed as a possible strategy to improve calcium intake. The objective of this study was to determine the sensory threshold of different calcium salts added to drinking water using survival analysis. Methods: We performed the triangle test methodology for samples of water with added calcium using three different calcium salts: calcium chloride, calcium gluconate and calcium lactate. For each salt, a panel of 54 consumers tested seven batches of three water samples. Data were adjusted for chance and sensory threshold was estimated using the survival methodology and a discrimination of 50%. Results: The threshold value estimation for calcium gluconate was 587 ± 131 mg/L of water, corresponding to 25% discrimination, for calcium lactate was 676 ± 186 mg/L, corresponding to 50% discrimination, and for calcium chloride was 291 ± 73 mg/L, corresponding to 50% discrimination. Conclusions: These results show that water with calcium added in different salts and up to a concentration of 500 mg of calcium/L of water is feasible. The calcium salt allowing the highest calcium concentration with the lowest perceived changes in taste was calcium gluconate. Future studies need to explore stability and acceptability over longer periods of time.

Testing for sensory threshold in drinking water with added calcium: a first step towards developing a calcium fortified water

Background: Food fortification is an effective strategy that has been recommended for improving population calcium inadequate intakes. Increasing calcium concentration of water has been proposed as a possible strategy to improve calcium intake. The objective of this study was to determine the sensory threshold of different calcium salts added to drinking water using survival analysis. Methods: We performed the triangle test methodology for samples of water with added calcium using three different calcium salts: calcium chloride, calcium gluconate and calcium lactate. For each salt, a panel of 54 consumers tested seven batches of three water samples. Data were adjusted for chance and sensory threshold was estimated using the survival methodology and a discrimination of 50%. Results: The threshold value estimation for calcium gluconate was 587 ± 131 mg/L of water, corresponding to 25% discrimination, for calcium lactate was 676 ± 186 mg/L, corresponding to 50% discrimination, and for calcium chloride was 291 ± 73 mg/L, corresponding to 50% discrimination. Conclusions: These results show that water with calcium added in different salts and up to a concentration of 500 mg of calcium/L of water is feasible. The calcium salt allowing the highest calcium concentration with the lowest perceived changes in taste was calcium gluconate. Future studies need to explore stability and acceptability over longer periods of time.

Estimation and comparison of the environmental impacts of acid mine drainage‐bearing river water in the Bor and Majdanpek porphyry copper mining areas in Eastern Serbia

AbstractMining activities in the Bor and Majdanpek mining areas in Eastern Serbia started in 1903 and 1961, respectively. Environmental problems in the Bor mining area began after the opening of the Bor mine. Long‐term pollution of river water in the Bor and Majdanpek mining areas has an environmental impact on East Europe because all of the river water from these mining areas flows into the Danube River. However, the sizes of areas with pollution and the differences between the environmental impacts of the Bor and Majdanpek mining areas are not clear. In order to determine the effects of mining activities on river water in the study area, creation of geochemical maps showing the distributions of sulfate, heavy metals, and arsenic; estimation of threshold values to discriminate anomalous values from background values; and comparison of the environmental impacts of the two mining areas were carried out. High concentrations of SO42−, Fe, As, Cu, and Mn were found in the Bor River, Krivelj River, and Bela River located in the Bor mining area. These rivers are characterized by acidic pH ranging from 2.9 to 6.2. High concentrations of these components were also measured in the Small Pek River and the upper reach of the Pek River. These rivers are located in the Majdanpek mining area and are characterized by weakly alkaline pH (7.3–8.4). The acidic river water in the Bor mining area transports large quantities of heavy metals and arsenic downstream (6,900 t/year of Fe, 42 t/year of As, 910 t/year of Cu, and 187 t/year of Mn). On the other hand, the weakly alkaline river water in the Majdanpek mining area transports smaller quantities of heavy metals and arsenic downstream (160 t/year of Fe, 0.1 t/year of As, 6 t/year of Cu, and 272 t/year of Mn). The environmental impact of the Bor mining area is significantly larger than that of the Majdanpek mining area. In addition, on the basis of the distribution of anomalous values in river water, pollution caused by mining activities reaches the Danube River, which is located more than 100 km from the Bor and Majdanpek mining areas. Concentrations of SO42−, Fe, As, Cu, and Mn in the Bela River in the Bor mining area have been greatly decreased after mixing of acidic polluted water of the Bela River with water of the Timok River containing a high bicarbonate concentration. This fact suggests that river water in the Bor and Majdanpek mining areas has sufficient capacity for neutralization. Considering appropriate countermeasures of environmental reclamation, such as artificial neutralization at some important sources of waste water before discharging the waste water from the mining sites, there is a possibility for environmental reclamation in both mining areas because unpolluted river water in the study area has sufficient capacity for neutralization in a natural system.

NO2 levels as a contributing factor to COVID-19 deaths: The first empirical estimate of threshold values

This study represents the first empirical estimation of threshold values between nitrogen dioxide (NO2) concentrations and COVID-19-related deaths in France. The concentration of NO2 linked to COVID-19-related deaths in three major French cities were determined using Artificial Neural Networks experiments and a Causal Direction from Dependency (D2C) algorithm. The aim of the study was to evaluate the potential effects of NO2 in spreading the epidemic. The underlying hypothesis is that NO2, as a precursor to secondary particulate matter formation, can foster COVID-19 and make the respiratory system more susceptible to this infection. Three different neural networks for the cities of Paris, Lyon and Marseille were built in this work, followed by the application of an innovative tool of cutting the signal from the inputs to the selected target. The results show that the threshold levels of NO2 connected to COVID-19 range between 15.8 μg/m3 for Lyon, 21.8 μg/m3 for Marseille and 22.9 μg/m3 for Paris, which were significantly lower than the average annual concentration limit of 40 μg/m³ imposed by Directive 2008/50/EC of the European Parliament.

Method of Calculating the Integral Indicator for Assessing Threats to the Economic Security of the Russian Federation

The paper analyzes and systematizes the basic catego-ries related with threats to the economic security of the Russian Federation, and establishes the relationship of their components in accordance with Federal regulatory legal documents. It provides an overview of the ap-proaches contained in the works of different authors in relation to the formation of the composition of threats to the economic security of the state and the assess-ment of their relevance. As a result, it is concluded that it is necessary to improve existing methods for as-sessing economic security threats for the national economy. The author’s method of calculating an inte-gral indicator for assessing threats to the economic security of the Russian Federation, based on a system of indicators grouped into clusters, is proposed. The initial approbation of the methodology was carried out on the basis of the author’s estimates of threshold val-ues and significance levels of indicators of economic security threats.

Determining thresholds of arsenic and mercury in stream sediment for mapping natural toxic element anomaly using data-driven models: a comparative study on probability plots and fractal methods

Natural toxic elements such as arsenic and mercury are widespread distributed in nature and the over accumulation of them usually has adverse effects on both environment and human beings. Therefore, to assess potential toxicity of these elements in natural environment such as water, soil, and stream sediment, it is significant to determine thresholds between anomalous and background geochemical data for identifying and mapping target areas with toxic element geochemical anomaly. In terms of data-driven, this study aims to demonstration of using the four statistical models that are box plot (BP), cumulative distribution function (CDF) diagram, concentration-number (C-N) fractal, and concentration-area (C-A) fractal methods to determine the threshold values of As and Hg in stream sediment for mapping their potential toxic anomaly in Pangxidong district, southwestern Guangdong, China, and compare the results critically. Firstly, a wide range of threshold values have been estimated by the four investigated data-driven methods. Then, the three threshold values of As and Hg that separate background data from low, moderate, and high geochemical anomalies determined by BP, CDF diagram, C-N fractal, and C-A fractal models were compared with the three level baselines defined in the Environmental Quality Standard for Soil in China (EQSSC). Furtherly, the geochemical anomaly maps of As and Hg were outlined by using the three threshold values to investigate the performance of the four data-driven methods in practical application of mapping natural toxic element anomaly. Finally, the contaminations of As and Hg in the study area were evaluated based on the suitable geochemical anomaly maps derived by the applicable data-driven method (i.e. CDF diagram). The main conclusions are that (1) of the four investigated data-driven methods, CDF diagram is the most suited for assist in the estimation of proper threshold values of As and Hg dividing geochemical background data from anomalies in the Pangxidong district; and (2) the contaminations of As mainly come from natural sources (i.e., bedrocks), while the contaminations of Hg are most likely to originate from anthropogenic factors (i.e., mining activities) in the Pangxidong district. The target areas, particular to the southern Wuling Reservoir, which have been identified with high As and Hg anomaly, probably should be taken effective measures to prevent the occurrences of pollution and toxicity from these elements.

Generation of 100-year-return value maps of maximum significant wave heights with automated threshold value estimation

Spectral numerical wave models are unable to predict extreme sea conditions accurately, and the probability of occurrence of a given wave parameter for fixed return periods (RPs) remains unexplored by such an approach. In this study, the significant wave height (SWH) parameter that plays a major role in ocean engineering and marine and naval activities was estimated spatially for the entire Bay of Bengal (BOB) region for the given RPs. Spatially gridded 44 years of SWH data at a spatial resolution of 1° × 1° were considered, and return value maps were generated for the BOB for 10-, 15-, 25-, 50-, and 100-year RPs. The peak over threshold (POT) model was chosen over a generalized Pareto distribution for data fitting and calculating the return values. As there is no existing method to determine the threshold value for use in the POT model, in this study, for the first time, an algorithm was designed to calculate the threshold value, which determined the accuracy of the estimation. Along with the conventional time-series analysis of the SWH data using POT, the novelty of the study lies in the spatial return period maps generated for the entire BOB region leading to the basin scale estimation.

An adaptive thresholding method for the wavelet based denoising of phonocardiogram signal

Abstract Segmentation of the phonocardiography (PCG) signal into cardiac cycles is a primary task for the diagnosis of cardiovascular diseases. However, PCG is highly susceptible to noise, and extra sound called murmur may also be present in the PCG signal due to pathology. These components cause difficulties in the segmentation and therefore, segmentation is often preceded by the denoising of the PCG signal to emphasize the fundamental heart sounds S1 and S2, by removing these unwanted components. For the denoising of the PCG signal, discrete wavelet transform (DWT) based algorithms have shown good performance because such algorithms suppress in-band noise besides the out-of-band noise. Selection of threshold value and threshold function significantly affects the performance of these algorithms. In this paper, for threshold value estimation, an adaptive method based on statistical parameters of the given PCG signal is proposed. The statistical parameters are found to be highly effective for this purpose. We also propose a new threshold function, non-linear mid function, to address the issues of SNR and transients in the existing threshold functions, soft and hard. The proposed method is applied on a large number of PCG signals with additive white Gaussian noise, red noise, and pink noise. The Performance of the proposed method is also evaluated on the PCG signals recorded in real-life noisy scenarios and signals with murmur sound. The obtained results show that the proposed method is significantly superior to the competitive algorithms.

Image De-Noising and Compression Using Statistical based Thresholding in 2-D Discrete Wavelet Transform

Images are very good information carriers but they depart from their original condition during transmission and are corrupted by different kind of noise. The purpose is to remove the noisy coefficients such that minimum amount of information is lost and maximum amount of noise is suppressed or reduced. We considered Generalized Gaussian distribution for modeling of noise. In the proposed technique, statistical thresholding methods are used for the estimation of threshold value while Bi-orthogonal wavelet has been envisaged for image decomposition and reconstruction. A qualitative and quantitative analysis of thresholding methods on different images shows significant results for statistical thresholding methods based on objective and subjective quality as compared to other de-noising methods.

Variability of estimated contamination extent depending on calculation methods

<p>The aim of research was to analyse the changes of contamination extent (E, %) estimated using two methods of background calculation by eliminating anomalies outside the interval mean±2s or median±2MAD (s is standard deviation, MAD is median absolute deviation) and optional normalisation. Two methods were used for estimation of background values (B) and upper threshold values (T) of Ag, As, Ba, Co, Cr, Cu, Mn, Mo, Ni, Pb, Sn, U, V, Zn and selected major elements according to their contents in topsoil samples from football fields in less contaminated districts of Klaipėda. Then two different sets of B and T values were applied to the whole geochemical data set. After determination of two sets of concentration coefficients (K<sub>k</sub>), four sets of enrichment factors were calculated: two simple (EF<sub>1</sub>) (normalisation by Al) and two complex (EF<sub>3</sub>) (normalisation by Al, K, Ti). </p><p>Estimation of E using T values resulted in lower percentage compared to percentage of sites where K<sub>k</sub>>1, EF<sub>1</sub>>1 or EF<sub>3</sub>>1, because the latter 3 indices depend on B values. Since all T values obtained by median±2MAD method are much lower (by 6-37.1%) than by mean±2s method, respective E is much higher: for 11 pollutants it is higher by more than 5% (range 6.3-34.2%). Since the absolute difference between B values estimated by two methods is much lower (only for Sn and Mn exceeds 5%) than the difference between T values, the influence of different B values on estimated E is much lower. Higher than 5% absolute difference between two sets of E estimated according to K<sub>k</sub>>1 is observed for 5 pollutants, according to EF<sub>3</sub>>1 for 4 and according to EF<sub>1</sub>>1 only for 3 pollutants. So E estimated according to EF<sub>1</sub>>1 is least of all influenced by the method of determination of B values, besides, it usually gives the highest E.</p>

Threshold Value Estimation Using Adaptive Two-Stage Plans inR

This paper introduces the R package twostageTE for estimation of an inverse regression function at a given point when one can sample an explanatory covariate at different values and measure the corresponding responses. The package implements a number of nonparametric methods for budget constrained threshold value estimation. Specifically, it contains methods for classical one-stage designs and also adaptive two-stage designs, which have been shown to yield more efficient and accurate results. A major advantage of the methods in package twostageTE is that threshold value estimation is performed without penalization or kernel smoothing, and hence, avoids the well-known problems of choosing the corresponding tuning parameter (regularization, bandwidth). The user can easily perform a two-stage analysis with twostageTE by (i) identifying the second stage sampling region from an initial sample, and (ii) computing various types of confidence intervals to ensure a robust analysis. The package twostageTE is illustrated through simulated examples.

Behavioral classification of data from collars containing motion sensors in grazing cattle

Remote monitoring of animal behavior offers great potential to improve livestock management however technologies able to collect data at high frequency and accurate data classification methods are required. The objective of this study was to develop a methodology capable of performing unsupervised behavioral classification of electronic data collected at high frequency from collar-mounted motion and GPS sensors in grazing cattle. Two independent trials were conducted, one for developing the classification algorithm (4 groups of 11 steers) and a second for its evaluation (14 steers). Each steer was fitted with a collar containing GPS and a 3-axis accelerometer that collected data at 4 and 10Hz, respectively. Foraging, ruminating, traveling, resting and ‘other active behaviors’ (which included scratching against objects, head shaking, and grooming) were observed and recorded continuously at the nearest second in animals wearing collars. Collar data were aggregated to 10-s intervals through the mean (indicative of the position of the neck and travel speed) and standard deviation (SD; indicative of activity level) and then log-transformed for analysis. The histograms of travel speed showed 3 populations and observations revealed these populations represented stationary, slow and fast travel behaviors. The histograms of the accelerometer X-axis mean showed populations corresponding with behaviors of head down or head up. The histograms of the accelerometer X-axis SD showed 3 populations representing behaviors with high, medium and low activity levels. Mixture models were fitted to data from each animal in both trials to calculate threshold values corresponding to where behaviors transitioned between different states. These thresholds from the 3 sensor signatures were then used in a decision tree to classify all 10-s data where behaviors were unknown into 5 mutually exclusive behaviors. The algorithm correctly classified 85.5% and 90.5% of all data points in the development and evaluation datasets, respectively. Foraging showed the greatest sensitivity (93.7% and 98.4%) and specificity (94.6% and 99.4%) followed by ruminating (sensitivity 97% and 87%, and specificity 90% and 95%) for development and evaluation trials, respectively. Major advantages of mixture models include computational efficiency suitable for large data sets (e.g. >2million data lines), minimal requirement for training datasets, and estimation of threshold values for individual animals under unknown and varying environmental conditions. The technology and methodology allows for the automatic and real-time monitoring of behavior with high spatial and temporal resolution which could benefit livestock industries beyond the research domain for improved animal and ecological management.

Calcifications Attenuation in Left Coronary Artery CT Images Using FDA Domain

The calcification plaque is a one kind of artifacts or noises, which is occurred in the Computed Tomography (CT) images as a very high attenuation coefficient. Computed Tomography (CT) images are more helpful than other modalities (e.g. Ultrasonic Imaging, Magnetic Resonance Imaging (MRI) etc.) for disease diagnosis but unfortunately, CT image is an affected sometime by calcification plaque. Medical image segmentation cannot be optimum because of having calcification in the CT images, which is absolutely unexpected. The calcification plaque is the major problem for optimal organ segmentation and detection. This proposed task is a subjective as well as an effective for calcification alleviation from CT images. In this paper, Firstly, we applied the Fisher's Discriminant Analysis (FDA) for optimal threshold value estimation. Secondly, the proposed optimal threshold value is used for the optimal threshold image extraction. After this, the morphological operation is used for heavy calcification erosion and the XOR operation is used for adjusting the optimal threshold image with the input image. Finally, we implemented the Extra-Energy Reduction (EER) Function to smooth the desired image. Therefore, our investigated method is the most significant and articulate in order to attenuate calcification plaque from CT images.

Estimation of the Threshold in Energy and Kurtosis Detectors for IR-UWB OOK Systems

In this paper, we propose a method to estimate the threshold value for energy detector (ED) and kurtosis detector (KD) in impulse radio ultra-wideband on-off keying (OOK) scheme. Estimation of threshold value is obtained from the parameters of the probability density functions (PDF) of two hypotheses in OOK signaling. Gaussian and lognormal distributions are used for ED receiver and KD receiver, respectively. Symbols are transmitted in packets and the PDF's parameters of the hypotheses are estimated by using training symbols in each packet. The approximation of the threshold value is obtained by using these parameters. Simulation results show that the estimated threshold has high accuracy for different amounts of signal to noise ratios and integration intervals.

Segmentation of SAR images using improved artificial bee colony algorithm and neutrosophic set

This paper proposes a novel synthetic aperture radar (SAR) image segmentation algorithm based on the neutrosophic set (NS) and improved artificial bee colony (I-ABC) algorithm. In this algorithm, threshold value estimation is considered as a search procedure that searches for a proper value in a grayscale interval. Therefore, I-ABC optimization algorithm is presented to search for the optimal threshold value. In order to get an efficient and powerful fitness function for I-ABC algorithm, the input SAR image is transformed into the NS domain. Then, a neutrosophic T and I subset images are obtained. A co-occurrence matrix based on the neutrosophic T and I subset images is constructed, and two-dimensional gray entropy function is described to serve as the fitness function of I-ABC algorithm. Finally, the optimal threshold value is quickly explored by the employed, onlookers and scouts bees in I-ABC algorithm. This paper contributes to SAR image segmentation in two aspects: (1) a hybrid model, having two different feature extraction methods, is proposed. (2) An optimal threshold value is automatically selected by maximizing the separability of the classes in gray level image by incorporating a simple and fast search strategy. The effectiveness of the proposed algorithm is demonstrated by application to real SAR images.