scholarly journals Parameter Estimation of Poisson–Gaussian Signal-Dependent Noise from Single Image of CMOS/CCD Image Sensor Using Local Binary Cyclic Jumping

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8330
Author(s):  
Jinyu Li ◽  
Yuqian Wu ◽  
Yu Zhang ◽  
Jufeng Zhao ◽  
Yingsong Si

Since signal-dependent noise in a local weak texture region of a noisy image is approximated as additive noise, the corresponding noise parameters can be estimated from a given set of weakly textured image blocks. As a result, the meticulous selection of weakly textured image blocks plays a decisive role to estimate the noise parameters accurately. The existing methods consider the finite directions of the texture of image blocks or directly use the average value of an image block to select the weakly textured image block, which can result in errors. To overcome the drawbacks of the existing methods, this paper proposes a novel noise parameter estimation method using local binary cyclic jumping to aid in the selection of these weakly textured image blocks. The texture intensity of the image block is first defined by the cumulative average of the LBCJ information in the eight neighborhoods around the pixel, and, subsequently, the threshold is set for selecting weakly textured image blocks through texture intensity distribution of the image blocks and inverse binomial cumulative function. The experimental results reveal that the proposed method outperforms the existing alternative algorithms by 23% and 22% for the evaluative measures of MSE (a) and MSE (b), respectively.

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2276 ◽  
Author(s):  
Yu Zhang ◽  
Guangyi Wang ◽  
Jiangtao Xu

Parameter estimation of Poisson-Gaussian signal-dependent random noise in the complementary metal-oxide semiconductor/charge-coupled device image sensor is a significant step in eliminating noise. The existing estimation algorithms, which are based on finding homogeneous regions, acquire the pair of the variances of noise and the intensities of every homogeneous region to fit the linear or piecewise linear curve and ascertain the noise parameters accordingly. In contrast to the existing algorithms, in this study, the Poisson noise samples of all homogeneous regions in every block image are pieced together to constitute a larger sample following the mixed Poisson noise distribution; then, the mean and variance of the mixed Poisson noise sample are deduced. Next, the mapping function among the noise parameters to be estimated—variance of Poisson-Gaussian noise and that of Gaussian noise corresponding to the stitched region in every block image—is constructed. Finally, the unbiased estimations of noise parameters are calculated from the mapping functions of all the image blocks. The experimental results confirm that the proposed method can obtain lower mean absolute error values of estimated noise parameters than the conventional ones.


2016 ◽  
Vol 52 ◽  
pp. 194-202
Author(s):  
S. L. Voitenko ◽  
L. V. Vishnevsky

The article shows the state of Ukrainian Whiteheaded cattle, which includes distribution of cattle, the number of animals belonging to respective bloodlines, evaluation of young animals with live weight in the process of growing and milk production of cows during the first lactation. It reflects the historic development of the breed when it was colonism whiteheaded cattle, which turned into the original breed, undergone a significant expansion in livestock and increase of productivity, decreased in the number, was as basis for creation of Ukrainian Black-and-White dairy breed and now bred only in one breeding farm. Visual estimation of animal exterior showed good development of cows and calves and their belonging to the dairy type. In the vast majority the cows of the herd have a black suit, a white head with " glasses" around the eyes, white belly, udder, lower legs and brush of the tail. The youngsters aren’t consolidated by the exterior, and among them there are animals which are not typical for Ukrainian Whiteheaded breed. The young animals have some lag in live weight behind the breed standard [12] to 7 months’ age with exceeding of this trait in certain periods quite significantly in the future. It was established that selection of heifers on live weight will be effective at the early age (1-5 months), given the coefficient of variation of live weight – 22,63-30,21% and will not have a significant influence in the future. Milk yields of first-calf heifers vary considerably depending on the origin. The milk yield of first-calf heifers in the herd was 4238,5 kg on average, the heifers belonging to Mart 171 and Ozon 417 bloodlines had the best milk performance – 4483,1 and 4254,9 kg accordingly. The most aligned milk yield during the first lactation was in the cows belonging to Ozon 417 bloodline, the limits of the trait are 4128,5-4327,4 kg with the average value by the line 4254,9 kg. In contrast, the first-calf heifers of Ryezvyi 33 bloodline with average milk yield 4048,9 kg had limits of the trait 2199,3-4736,1 kg. Even greater range in cows’ milk yield during the first lactation R= 4939 kg (limits 1687 – 6626 kg) is characterized for the herd in general, it shows, on the one hand, the possibility of qualitative improvement of cows’ productivity due to selection on the investigated trait and lack of selection in the herd on the other hand. It was established that daughters of bull Chardash belonging to Ryezvyi 33 bloodline produced 4736,1 kg of milk for 305 days of the first lactation with fat content 3,6%, whereas Zlak’s descendants of the same line were characterized by the lowest milk yield for the first completed lactation – 2199,3 kg with fat content 3,7% and the average value by the line – 4048,9 kg of milk, fat content 3,6%. Similar variability of first-calf heifers’ milk yields, depending on the origin, is typical for other bloodlines of Ukrainian Whiteheaded breed. To increase milk productivity of Ukrainian Whiteheaded cows is recommended to repeat successful combinations of parental forms, and to preserve the breed – to carry out an objective assessment of animals by a range of traits, given the efficiency of selection of heifers on live weight at early age.


SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110269
Author(s):  
Lang Liang

The Bass model is the most popular model for forecasting the diffusion process of a new product. However, the controlling parameters in it are unknown in practice and need to be determined in advance. Currently, the estimation of the controlling parameters has been approached by various techniques. In this case, a novel optimization-based parameter estimation (OPE) method for the Bass model is proposed in the theoretical framework of system dynamics ( SD). To do this, the SD model of the Bass differential equation is first established and then the corresponding optimization mathematical model is formulated by introducing the controlling parameters as design variable and the discrepancy of the adopter function to the reference value as objective function. Using the VENSIM software, the present SD optimization model is solved, and its effectiveness and accuracy are demonstrated by two examples: one involves the exact solution and another is related to the actual user diffusion problem from Chinese Mobile. The results show that the present OPE method can produce higher predicting accuracy of the controlling parameters than the nonlinear weighted least squares method and the genetic algorithms. Moreover, the reliability interval of the estimated parameters and the goodness of fitting of the optimal results are given as well to further demonstrate the accuracy of the present OPE method.


2021 ◽  
Vol 11 (2) ◽  
pp. 466
Author(s):  
Włodzimierz Kęska ◽  
Jacek Marcinkiewicz ◽  
Łukasz Gierz ◽  
Żaneta Staszak ◽  
Jarosław Selech ◽  
...  

The continuous development of computer technology has made it applicable in many scientific fields, including research into a wide range of processes in agricultural machines. It allows the simulation of very complex physical phenomena, including grain motion. A recently discovered discrete element method (DEM) is used for this purpose. It involves direct integration of equations of grain system motion under the action of various forces, the most important of which are contact forces. The method’s accuracy depends mainly on precisely developed mathematical models of contacts. The creation of such models requires empirical validation, an experiment that investigates the course of contact forces at the moment of the impact of the grains. To achieve this, specialised test stations equipped with force and speed sensors were developed. The correct selection of testing equipment and interpretation of results play a decisive role in this type of research. This paper focuses on the evaluation of the force sensor dynamic properties’ influence on the measurement accuracy of the course of the plant grain impact forces against a stiff surface. The issue was examined using the computer simulation method. A proprietary computer software with the main calculation module and data input procedures, which presents results in a graphic form, was used for calculations. From the simulation, graphs of the contact force and force signal from the sensor were obtained. This helped to clearly indicate the essence of the correct selection of parameters used in the tests of sensors, which should be characterised by high resonance frequency.


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