scholarly journals Star Sensor Denoising Algorithm Based on Edge Protection

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5255
Author(s):  
Kaili Lu ◽  
Enhai Liu ◽  
Rujin Zhao ◽  
Hui Zhang ◽  
Hong Tian
Keyword(s):  
Image Denoising ◽  
Estimation Error ◽  
Experimental Results ◽  
Star Sensor ◽  
Side Window ◽  
Star Image ◽  
Centroid Estimation ◽  
Single Pixel

Single-pixel noise commonly appearing in a star sensor can cause an unexpected error in centroid extraction. To overcome this problem, this paper proposes a star image denoising algorithm, named Improved Gaussian Side Window Filtering (IGSWF). Firstly, the IGSWF algorithm uses four special triangular Gaussian subtemplates for edge protection. Secondly, it exploits a reconstruction function based on the characteristic of stars and noise. The proposed IGSWF algorithm was successfully verified through simulations and evaluated in a star sensor. The experimental results indicated that the IGSWF algorithm performed better in preserving the shape of stars and eliminating the single-pixel noise and the centroid estimation error (CEE) value after using the IGSWF algorithm was eight times smaller than the original value, six times smaller than that after traditional window filtering, and three times smaller than that after the side window filtering.

scholarly journals Processing Centroids of Smearing Star Image of Star Sensor

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yufu Liao ◽  
Enhai Liu ◽  
Jianyong Zhong ◽  
Hui Zhang
Keyword(s):  
Angular Rate ◽  
Analytical Form ◽  
Integration Time ◽  
Star Sensor ◽  
Centre Of Mass ◽  
Image Model ◽  
Star Image ◽  
Centroid Estimation ◽  
Novel Method ◽  
Better Than

A novel method was presented for increasing the accuracy of subpixel centroid estimation for smearing star image. Model of the smearing trajectory of smearing star was built. It helped to study the analytical form of the errors, caused by image smearing, for centroid estimation. In the algorithm, the errors were estimated with accuracy and used to revise the centroid processed by CoM (centre of mass). Simulations have been run to study the effect of angular rates, integration time, and actual position of star on the accuracy of centroid estimation. Results were presented which suggested that the proposed algorithm had a precision better than 1/10 of a pixel when the angular rate was up to 3.0 deg/s.

Crack Grid Detection and Calculation Based on Convolutional Neural Network

2021 ◽  
Author(s):  
Liyang Xiao ◽  
Wei Li ◽  
Ju Huyan ◽  
Zhaoyun Sun ◽  
Susan Tighe
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Convolutional Neural Network ◽  
Image Denoising ◽  
Crack Detection ◽  
Experimental Results ◽  
Crack Identification ◽  
Threshold Segmentation ◽  
Improve Image Quality

This paper aims to develop a method of crack grid detection based on convolutional neural network. First, an image denoising operation is conducted to improve image quality. Next, the processed images are divided into grids of different, and each grid is fed into a convolutional neural network for detection. The pieces of the grids with cracks are marked and then returned to the original images. Finally, on the basis of the detection results, threshold segmentation is performed only on the marked grids. Information about the crack parameters is obtained via pixel scanning and calculation, which realises complete crack detection. The experimental results show that 30×30 grids perform the best with the accuracy value of 97.33%. The advantage of automatic crack grid detection is that it can avoid fracture phenomenon in crack identification and ensure the integrity of cracks.

scholarly journals Star Image Prediction and Restoration under Dynamic Conditions

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1890 ◽  
Author(s):  
Liu ◽  
Chen ◽  
Liu ◽  
Shi
Keyword(s):  
Attitude Control ◽  
Attitude Determination ◽  
Back Propagation ◽  
Prediction Method ◽  
Back Propagation Neural Network ◽  
Attitude Measurement ◽  
Star Sensor ◽  
Dynamic Conditions ◽  
Star Image ◽  
Image Prediction

The star sensor is widely used in attitude control systems of spacecraft for attitude measurement. However, under high dynamic conditions, frame loss and smearing of the star image may appear and result in decreased accuracy or even failure of the star centroid extraction and attitude determination. To improve the performance of the star sensor under dynamic conditions, a gyroscope-assisted star image prediction method and an improved Richardson-Lucy (RL) algorithm based on the ensemble back-propagation neural network (EBPNN) are proposed. First, for the frame loss problem of the star sensor, considering the distortion of the star sensor lens, a prediction model of the star spot position is obtained by the angular rates of the gyroscope. Second, to restore the smearing star image, the point spread function (PSF) is calculated by the angular velocity of the gyroscope. Then, we use the EBPNN to predict the number of iterations required by the RL algorithm to complete the star image deblurring. Finally, simulation experiments are performed to verify the effectiveness and real-time of the proposed algorithm.

scholarly journals A Luenberger-Like Observer for Multistable Kapitaniak Chaotic System

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
J. Humberto Pérez-Cruz ◽  
Jacobo Marcos Allende Peña ◽  
Christian Nwachioma ◽  
Jose de Jesus Rubio ◽  
Jaime Pacheco ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Chaotic System ◽  
Estimation Error ◽  
Lipschitz Constant ◽  
Experimental Results ◽  
Good Agreement

The objective of this paper is to estimate the unmeasurable variables of a multistable chaotic system using a Luenberger-like observer. First, the observability of the chaotic system is analyzed. Next, a Lipschitz constant is determined on the attractor of this system. Then, the methodology proposed by Raghavan and the result proposed by Thau are used to try to find an observer. Both attempts are unsuccessful. In spite of this, a Luenberger-like observer can still be used based on a proposed gain. The performance of this observer is tested by numerical simulation showing the convergence to zero of the estimation error. Finally, the chaotic system and its observer are implemented using 32-bit microcontrollers. The experimental results confirm good agreement between the responses of the implemented and simulated observers.

Region-confined restoration method for motion-blurred star image of the star sensor under dynamic conditions

2016 ◽  
Vol 55 (17) ◽  
pp. 4621 ◽  
Author(s):  
Liheng Ma ◽  
Franco Bernelli-Zazzera ◽  
Guangwen Jiang ◽  
Xingshu Wang ◽  
Zongsheng Huang ◽  
...  
Keyword(s):  
Star Sensor ◽  
Dynamic Conditions ◽  
Star Image ◽  
Restoration Method

scholarly journals Image Denoising Based on Dilated Singularity Prior

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Shaoxiang Hu ◽  
Zhiwu Liao ◽  
Wufan Chen
Keyword(s):  
Em Algorithm ◽  
Image Denoising ◽  
Mathematical Morphology ◽  
Visual Quality ◽  
Spatial Domain ◽  
Experimental Results ◽  
Canny Operator ◽  
Nonlocal Means ◽  
Spatial Image ◽  
Noisy Images

In order to preserve singularities in denoising, we propose a new scheme by adding dilated singularity prior to noisy images. The singularities are detected by canny operator firstly and then dilated using mathematical morphology for finding pixels “near” singularities instead of “on” singularities. The denoising results for pixels near singularities are obtained by nonlocal means in spatial domain to preserve singularities while the denoising results for pixels in smooth regions are obtained by EM algorithm constrained by a mask formed by downsampled spatial image with dilated singularity prior to suiting the sizes of the subbands of wavelets. The final denoised results are got by combining the above two results. Experimental results show that the scheme can preserve singularity well with relatively high PSNR and good visual quality.

Single pixel star sensor

2016 ◽  
Author(s):  
Ran Yang ◽  
Mingfei Li ◽  
Juan Huo ◽  
Lianjie Zhao ◽  
Anning Zhang ◽  
...  
Keyword(s):  
Star Sensor ◽  
Single Pixel
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