Motion Blurred Image Restoration Algorithm Based on AGA and Wiener Filter in Ship Imaging System

2013 ◽  
Vol 753-755 ◽  
pp. 3005-3008
Author(s):  
Sheng Liu ◽  
Meng Jun Wang ◽  
Hui Xuan Fu
Keyword(s):  
Genetic Algorithm ◽  
Image Restoration ◽  
Imaging System ◽  
Wiener Filter ◽  
Convergence Time ◽  
Adaptive Genetic Algorithm ◽  
Crossover Probability ◽  
Blurred Image ◽  
Blurred Images ◽  
Ringing Effect

Ship internal equipment vibration will cause the imaging system platform vibration, resulting in blurred images. Wiener Filter is often used to restore the motion blurred image. The principle of the method expects to minimize the mean square error between the restore image and original image. However, this method has some constrains, and it generates ringing effect easily. In order to get high quality restore image, eliminate the ringing effect, a new approach based on an adaptive genetic algorithm (AGA) Wiener Filter was proposed, which automatically adjusts the SNR parameter value for Wiener Filter, this method selects crossover probability and mutation probability according to the fitness values of the object function, therefore reduces the convergence time and improves the precision of simple genetic algorithm (SGA), insuring the accuracy of parameter selection, effectively reducing the ringing effect after image restoration, improve image quality of restoration.

Restoration of Motion Blurred Image Based on PSO Combine Wiener Filter in Ship Imaging System

2014 ◽  
Vol 1006-1007 ◽  
pp. 739-742
Author(s):  
Hui Xuan Fu ◽  
Yu Chao Wang ◽  
Xun Su
Keyword(s):  
Imaging System ◽  
Search Algorithm ◽  
Wiener Filter ◽  
Optimal Solution ◽  
Parameter Selection ◽  
Improve Image Quality ◽  
Blurred Image ◽  
Blurred Images ◽  
Ringing Effect

Ship internal equipment vibration will cause the imaging system platform vibration, resulting in blurred images. Wiener Filter is often used to restore the motion blurred image. The principle of the method expects to minimize the mean square error between the restore image and original image. However, this method has some constrains, if parameter selection improper, it generates ringing effect easily. Usually, most users select parameter by rule of thumb, so they frequently fail to generate the optimal solution. In order to get high quality restore image, eliminate the ringing effect, a new approach based on particle swarm optimization (PSO) Wiener Filter was proposed, which automatically adjusts the parameter for Wiener Filter, this method seek the optimal solution by transferring information between individuals and information sharing, which is a highly efficient parallel search algorithm, insuring the accuracy of parameter selection, effectively reducing the ringing effect after image restoration, improve image quality of restoration.

scholarly journals Restoration for Motion Blurred Images of Moving Objects

2012 ◽  
Vol 6-7 ◽  
pp. 1108-1111
Author(s):  
Gui Xiang Zhou
Keyword(s):  
Image Restoration ◽  
Moving Objects ◽  
Wiener Filter ◽  
Parameter Analysis ◽  
Blurred Image ◽  
Probability And Statistics ◽  
Blurred Images ◽  
Ringing Effect ◽  
Transportation Applications ◽  
Error Parameter

Image restoration plays an important role in transportation applications. This paper studies a motion blurred image processing method, which has good recovery effect. In this method, first the wiener filter is used for image restoration. Then, based on the error parameter analysis, the parameters of point spread function are estimated, and the noise parameter is estimated by using the probability and statistics method. Furthermore, the ringing effect is processed by using the smooth boundary method. Finally, experimental results show that the proposed method can restore the motion blurred images effectively and has strong robustness for the noise.

Research on the Optimization of the Numerical Value Based on Improved Genetic Algorithm

2013 ◽  
Vol 333-335 ◽  
pp. 1256-1260
Author(s):  
Zhen Dong Li ◽  
Qi Yi Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Adaptive Genetic Algorithm ◽  
Improved Genetic Algorithm ◽  
Adaptive Genetic Algorithms ◽  
Crossover Probability ◽  
Adaptive Crossover ◽  
Searching Ability ◽  
New Algorithms ◽  
Relevance Index

For the lack of crossover operation, from three aspects of crossover operation , systemically proposed one kind of improved Crossover operation of Genetic Algorithms, namely used a kind of new consistent Crossover Operator and determined which two individuals to be paired for crossover based on relevance index, which can enhance the algorithms global searching ability; Based on the concentrating degree of fitness, a kind of adaptive crossover probability can guarantee the population will not fall into a local optimal result. Simulation results show that: Compared with the traditional cross-adaptive genetic Algorithms and other adaptive genetic algorithm, the new algorithms convergence velocity and global searching ability are improved greatly, the average optimal results and the rate of converging to the optimal results are better.

Fast Restoration Algorithm for Rotational Motion Blurred Images

2011 ◽  
Vol 267 ◽  
pp. 969-973
Author(s):  
Jian Yang Zhou ◽  
Yin Tao Yang ◽  
Yi Liang Wu
Keyword(s):  
Image Restoration ◽  
Rotational Motion ◽  
Fast Algorithm ◽  
Degradation Model ◽  
Experimental Platform ◽  
Restoration Algorithm ◽  
Blurred Image ◽  
Comparison And Analysis ◽  
Blurred Images ◽  
Image Degradation Model

This paper first introduces the history and research status of motion-blurred image restoration, and then establishes a rotating image degradation model. we present a fast algorithm for real-time hardware restoration of rotating motion blurred images, the algorithm is simulated and experimental platform is built for the actual verification. Through comparison and analysis of the recovery results, we verify the accuracy of the algorithm, and it shows that this rotational motion blurred image restoration algorithm can receive satisfactory results.

A Research on the Optimization of Fuzzy Image

2013 ◽  
Vol 409-410 ◽  
pp. 1593-1596
Author(s):  
Xue Feng Wu ◽  
Yu Fan
Keyword(s):  
Mathematical Model ◽  
Image Restoration ◽  
Point Spread Function ◽  
Motion Blur ◽  
Inverse Filtering ◽  
Point Spread ◽  
Spread Function ◽  
Blurred Image ◽  
Blurred Images ◽  
Fuzzy Image

The restore algorithm of the image blurred by motion is proposed, and a mathematical model based on motion blur system is eomtrueted£®The Point spread function of the motion blur is given According to the characteristics of blurred images the parameters of point spread function are estimated ,and three methods are introduced for image restoration. The three methods are inverse filtering of image restoration, Lucy-Richardson image restoration and Wiener image restoration. The principles of the three image restoration methods are analyzed. The motion blurred image restoration experiment is made. The results show that the visibility of the image is improved, and the image restoration is more stable.

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.

The Restoration of Motion Blurred Images Based on the Background Modeling

2014 ◽  
Vol 687-691 ◽  
pp. 3591-3595
Author(s):  
Jiang Yang Chen ◽  
Xi Ling Luo
Keyword(s):  
Wiener Filter ◽  
Background Modeling ◽  
Motion Blur ◽  
Edge Density ◽  
Image Generation ◽  
Point Spread ◽  
Spread Function ◽  
Blurred Image ◽  
Image Area ◽  
Blurred Images

For the mutual effects of camera shake and subject movement, the image generation space varying motion blur. In order to achieve image restoration, firstly dividing the image area using the Gaussian background modeling, and updated model adaptive to improve the speed and convergence accuracy. Then use the total variation (TV) of the L1 model to estimate the regional point spread function (PSF), and adopted the edge density weight to reduce small edge’s interference for the PSF estimates. Eventually to restored image by Wiener filter. Through experimental analysis, compared with other algorithms, our algorithms get better results in the space varies motion-blurred image.

scholarly journals Image Deblurring using Wiener Filtering and Siamese Neural Network

2021 ◽  
Vol 9 (3) ◽  
pp. 96
Author(s):  
Vaibhav Setia ◽  
Shreya Kumar
Keyword(s):  
Neural Network ◽  
Image Matching ◽  
Signal To Noise Ratio ◽  
Wiener Filter ◽  
Function Estimation ◽  
Point Spread ◽  
Spread Function ◽  
Blurred Image ◽  
Blurred Images ◽  
Local Image

Blurred images are difficult to avoid in situations when minor Atmospheric turbulence or camera movement results in low-quality images. We propose a system that takes a blurred image as input and produces a deblurred image by utilizing various filtering techniques. Additionally, we utilize the Siamese Network to match local image segments. A Siamese Neural Network model is used that is trained to account for image matching in the spatial domain. The best-matched image returned by the model is then further used for Signal-to-Noise ratio and Point Spread Function estimation. The Wiener filter is then used to deblur the image. Finally, the results of the deblurring techniques with existing algorithms are compared and it is shown that the error in deblurring an image using the techniques presented in this paper is considerably lesser than other techniques.

scholarly journals Optimasi Biaya Distribusi Rantai Pasok Tiga Tingkat dengan Menggunakan Algoritma Genetika Adaptif dan Terdistribusi

2014 ◽  
Vol 10 (1) ◽  
pp. 189
Author(s):  
Zulfahmi Indra ◽  
Subanar Subanar
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Migration Rate ◽  
Adaptive Genetic Algorithm ◽  
Chain Management ◽  
Stepping Stone ◽  
Mutation Probability ◽  
Crossover Probability ◽  
Distributed Genetic Algorithm

AbstrakManajemen rantai pasok merupakan hal yang penting. Inti utama dari manajemen rantai pasok adalah proses distribusi. Salah satu permasalahan distribusi adalah strategi keputusan dalam menentukan pengalokasian banyaknya produk yang harus dipindahkan mulai dari tingkat manufaktur hingga ke tingkat pelanggan. Penelitian ini melakukan optimasi rantai pasok tiga tingkat mulai dari manufaktur-distributor-gosir-retail. Adapun pendekatan yang dilakukan adalah algoritma genetika adaptif dan terdistribusi. Solusi berupa alokasi banyaknya produk yang dikirim pada setiap tingkat akan dimodelkan sebagai sebuah kromosom. Parameter genetika seperti jumlah kromosom dalam populasi, probabilitas crossover dan probabilitas mutasi akan secara adaptif berubah sesuai dengan kondisi populasi pada generasi tersebut. Dalam penelitian ini digunakan 3 sub populasi yang bisa melakukan pertukaran individu setiap saat sesuai dengan probabilitas migrasi. Adapun hasil penelitian yang dilakukan 30 kali untuk setiap perpaduan nilai parameter genetika menunjukkan bahwa nilai biaya terendah yang didapatkan adalah 80,910, yang terjadi pada probabilitas crossover 0.4, probabilitas mutasi 0.1, probabilitas migrasi 0.1 dan migration rate 0.1. Hasil yang diperoleh lebih baik daripada metode stepping stone yang mendapatkan biaya sebesar 89,825. Kata kunci— manajemen rantai pasok, rantai pasok tiga tingkat, algortima genetika adaptif, algoritma genetika terdistribusi. Abstract Supply chain management is critical in business area. The main core of supply chain management is the process of distribution. One issue is the distribution of decision strategies in determining the allocation of the number of products that must be moved from the level of the manufacture to the customer level. This study take optimization of three levels distribution from manufacture-distributor-wholeshale-retailer. The approach taken is adaptive and distributed genetic algorithm. Solution in the form of allocation of the number of products delivered at each level will be modeled as a chromosome. Genetic parameters such as the number of chromosomes in the population, crossover probability and adaptive mutation probability will change adaptively according to conditions on the population of that generation. This study used 3 sub-populations that exchange individuals at any time in accordance with the probability of migration. The results of research conducted 30 times for each value of the parameter genetic fusion showed that the lowest cost value obtained is 80,910, which occurs at the crossover probability 0.4, mutation probability 0.1, the probability of migration 0.1 and migration rate 0.1. This result has shown that adaptive and distributed genetic algorithm is better than stepping stone method that obtained 89,825. Keywords— management supply chain, three level supply chain, adaptive genetic algorithm, distributed genetic algorithm.

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