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Fuzzy Multilevel Image thresholding Based on Modified Quick Artificial Bee Colony Algorithm and Local Information Aggregation

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-18页

作者： Li, Linguo Sun, Lijuan Guo, Jian Han, Chong Li, Shujing Nanjing Univ Posts & Telecommun Sch Comp Nanjing 210003 Jiangsu Peoples R China Fuyang Normal Univ Coll Informat Engn Fuyang 236041 Peoples R China Nanjing Univ Posts & Telecommun Jiangsu High Technol Res Key Lab Wireless Sensor Nanjing 210003 Jiangsu Peoples R China

thresholding segmentation based on fuzzy entropy and intelligent optimization is one of the most commonly used and direct methods. This paper takes fuzzy Kapur's entropy as the best optimal objective function, with modified quick artificial bee colony algorithm (MQABC) as the tool, performs fuzzy membership initialization operations through Pseudo Trapezoid-Shaped (PTS) membership function, and finally, according to the image's spacial location information, conducts local information aggregation by way of median, average, and iterative average so as to achieve the final segmentation. The experimental results show that the proposed FMQABC (fuzzy based modified quick artificial bee colony algorithm) and FMQABCA (fuzzy based modified quick artificial bee colony and aggregation algorithm) can search out the best optimal threshold very effectively, precisely, and speedily and in particular show exciting efficiency in running time. This paper experimentally compares the proposedmethod with Kapur's entropy-based Electromagnetism Optimization (EMO) method, standard ABC, and FDE (fuzzy entropy based differential evolution algorithm), respectively, and concludes that MQABCA is far more superior to the rest in terms of segmentation quality, iterations to convergence, and running time.

关键词： BEES algorithm MEMBERSHIP functions (Fuzzy logic) thresholding algorithms SEGMENTATION (Image processing) INFORMATION storage & retrieval systems

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The influence of filtration and decomposition window size on the threshold value and accuracy of land-cover classification of polarimetric SAR images

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2016年第1期37卷 212-228页

作者： Wozniak, Edyta Kofman, Wlodek Wajer, Pawel Lewinski, Stanislaw Nowakowski, Artur Polish Acad Sci Earth Observat Grp Space Res Ctr PL-00716 Warsaw Poland CNRS IPAG Inst Planetol & Astrophys Grenoble F-38000 Grenoble France

In this study we use ALOS PALSAR satellite data to classify land cover using a decision tree algorithm. We apply polarimetric decomposition methods to coherence and covariance matrices obtained from the data and then use threshold values to classify terrain. We evaluate the influence of speckle filter and decomposition window sizes on the threshold value used in the decision algorithm and on the accuracy of the classification. We also study the sensitivity of the classification to the accuracy of the threshold value. First, we processed a fully polarimetric Synthetic Aperture Radar (SAR) L-band image using different sizes of speckle filtration and decomposition window (3 x 3 pixels, 5 x 5, 7 x 7, 9 x 9), and the decomposition methods available in PolSARPro software. We evaluated these methods and chose the most efficient. Then we developed a simple hierarchical classification scheme based on threshold values. In the first step we divided the terrain into smooth and rough areas and then separated these into more detailed subclasses (water and agriculture, and forest and urban) which correspond to smooth and rough areas, respectively. A more detailed analysis separated continuous and discontinuous urban fabric and deciduous and coniferous forests. The maximum overall accuracy of the classification was 86.1% for the four main land cover classes, and 80.4% for the six more detailed classes. The accuracy of the classification dropped by about 10% when nonoptimal window sizes were used in image filtration or decomposition.

关键词： LAND cover INFORMATION filtering systems CLASSIFICATION algorithms SYNTHETIC aperture radar thresholding algorithms

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PHOTOELECTRIC EFFECT FOR TWIST-DEFORMED SPACE-TIME

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ACTA PHYSICA POLONICA B 2016年第5期47卷 1293-1299页

作者： Daszkiewicz, Marcin Univ Wroclaw Inst Theoret Phys Pl Maxa Borna 9 PL-50206 Wroclaw Poland

In this article, we investigate the impact of twisted space-time on the photoelectric effect, i.e., we derive the theta-deformed threshold frequency. In such a way, we indicate that the space-time noncommutativity str... 详细信息

关键词： Photoelectric effect Twistor theory Space & time thresholding algorithms Numerical analysis

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A New Wavelet Threshold Function and Denoising Application

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-8页

作者： Lu Jing-yi Lin Hong Ye Dong Zhang Yan-sheng Harbin Inst Technol Sch Elect Engn & Automat Harbin 150001 Peoples R China Northeast Petr Univ Fac Elect & Informat Engn Daqing 163318 Peoples R China

In order to improve the effects of denoising, this paper introduces the basic principles of wavelet threshold denoising and traditional structures threshold functions. Meanwhile, it proposes wavelet threshold function and fixed threshold formula which are both improved here. First, this paper studies the problems existing in the traditional wavelet threshold functions and introduces the adjustment factors to construct the new threshold function basis on soft threshold function. Then, it studies the fixed threshold and introduces the logarithmic function of layer number of wavelet decomposition to design the new fixed threshold formula. Finally, this paper uses hard threshold, soft threshold, Garrote threshold, and improved threshold function to denoise different signals. And the paper also calculates signal-to-noise (SNR) and mean square errors (MSE) of the hard threshold functions, soft thresholding functions, Garrote threshold functions, and the improved threshold function after denoising. Theoretical analysis and experimental results showed that the proposed approach could improve soft threshold functions with constant deviation and hard threshold with discontinuous function problems. The proposed approach could improve the different decomposition scales that adopt the same threshold value to deal with the noise problems, also effectively filter the noise in the signals, and improve the SNR and reduce the MSE of output signals.

关键词： WAVELETS (Mathematics) SIGNAL denoising thresholding algorithms SIGNAL-to-noise ratio MEAN square algorithms

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-12页

作者： Kang, Ruirui Qu, Gangrong Cao, Bin Yan, Long Beijing Jiaotong Univ Sch Sci Beijing 100044 Peoples R China Beijing Ctr Math & Informat Interdisciplinary Sci Beijing 100048 Peoples R China Xiangtan Univ Coll Informat Engn Xiangtan 411105 Peoples R China Yanan City Peoples Hosp MRI CT Diag Branch Baota Dist 716000 Shaanxi Peoples R China

It is challenging to save acquisition time and reconstruct a medical magnetic resonance (MR) image with important details and features from its compressive measurements. In this paper, a novel method is proposed for longitudinal compressive sensing (LCS) MR imaging (MRI), where the similarity between reference and acquired image is combined with joint sparsifying transform. Furthermore, the joint sparsifying transform with the wavelet and the Contourlet can efficiently represent both isotropic and anisotropic features and the objective function is solved by extended smooth-based monotone version of the fast iterative shrinkage thresholding algorithm (SFISTA). The experiment results demonstrate that the existing regularization model obtains better performance with less acquisition time and recovers both edges and fine details of MR images, much better than the existing regularization model based on the similarity and the wavelet transform for LCS-MRI.

关键词： COMPRESSED sensing (Signal processing) MAGNETIC resonance imaging WAVELET transforms thresholding algorithms REGULARIZATION (Mathematics)

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Enhancement of SAR images using curvelet with controlled shrinking technique

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REMOTE SENSING LETTERS 2016年第1期7卷 21-30页

作者： Puranikmath, Shivakumara Swamy Kaliyaperumal, Vani Anna Univ Dept Informat Sci & Technol Madras 600025 Tamil Nadu India

The speckle noise is the primary constraint in synthetic aperture radar (SAR) images. It will affect the features in the image and cause misinterpretation of objects. In this letter, curvelet with controlled shrinking technique is proposed to suppress speckle noise in SAR images. In this method, the curvelet transform is applied to SAR image. It decomposes image into different levels based on frequency. Application of using threshold and controlled shrinking function in the curvelet transform suppresses the noise coefficients. The results are favourable compared with some traditional techniques in terms of performance as well as preserving the details of the image.

关键词： SYNTHETIC aperture radar CURVELET transforms SPECKLE noise SPATIAL filters thresholding algorithms

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Codimension One Threshold Manifold for the Critical gKdV Equation

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COMMUNICATIONS IN MATHEMATICAL PHYSICS 2016年第3期342卷 1075-1106页

作者： Martel, Yvan Merle, Frank Nakanishi, Kenji Raphael, Pierre Ecole Polytech CMLS CNRS UMR7640 F-91128 Palaiseau France Univ Cergy Pontoise F-95302 Cergy Pontoise France Inst Hautes Etud Sci CNRS AGM UMR8088 F-95302 Cergy Pontoise France Kyoto Univ Dept Math Kyoto 6068502 Japan Univ Nice Sophia Antipolis Lab JA Dieudonne CNRS UMR7351 F-06108 Nice 02 France

We construct the "threshold manifold" near the soliton for the mass critical gKdV equation, completing results obtained in Martel et al. (Acta Math 212:59-140, 2014, J Math Eur Soc 2015). In a neighborhood of the soliton, this C (1) manifold of codimension one separates solutions blowing up in finite time and solutions in the "exit regime". On the manifold, solutions are global in time and converge locally to a soliton. In particular, the soliton behavior is strongly unstable by blowup.

关键词： thresholding algorithms MANIFOLDS (Mathematics) NUMERICAL solutions to equations DIMENSIONAL analysis SOLITONS

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Self-Adjusting Cutting Parameter Technique for Drilling Multi-Stacked Material

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SAE INTERNATIONAL JOURNAL OF MATERIALS AND MANUFACTURING 2016年第1期9卷 24-30页

作者： Jallageas, Jeremy Ayfre, Matthieu Cherif, Mehdi K'nevez, Jean-Yves Cahuc, Olivier NOOV Technol Biscarrosse France Aquitaine Sci Transfert Talence France Univ Bordeaux Bordeaux France

This study investigates the self-adjusted cutting parameter technique to improve the drilling of multi-stacked material. The technique consists in changing the cutting strategy automatically, according to the material being machined. The success of this technique relies on an accurate signal analysis, whatever the process setting. Motor current or thrust force are mostly used as incoming signals. Today, analyses are based on the thresholding method. This consists in assigning lower and upper limits for each type of material. The material is then identified when the signal level is stabilized in between one of the thresholds. Good results are observed as long as signal steps are significantly distinct. This is the case when drilling TA6V-CFRP stacks. However, thrust force level remains roughly unchanged for AA7175-CFRP stacks, leading to overlapping thresholds. These boundary limits may also change with tool geometry, wear condition, cutting parameters, etc. The thresholding method is therefore not optimal for industrial uses. The paper presents a new method, able to differentiate composites from metallic materials, in real-time and independently of any process parameters (drill geometry, tool wear, etc.). The proposed approach based on Discrete Wavelet Transform (DWT) is able to detect specific frequency characteristics generated by material cutting. Using this method, improvements can be made to the self-adjusted cutting parameter technique for multi-stacked drilling application. Results are validated experimentally using thrust force signals measured while drilling various multi-materials under different process parameters.

关键词： DRILLING & boring thresholding algorithms AUTOMATION THRUST CUTTING (Materials) BOUNDARY value problems

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Shoreline change assessment for various types of coasts using multi-temporal Landsat imagery of the east coast of South Korea

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REMOTE SENSING LETTERS 2016年第1期7卷 91-100页

作者： Choung, Yun-Jae Jo, Myung-Hee Geo C&I Co Ltd Res Inst Spatial Informat Technol Daegu South Korea Kyungpook Natl Univ Sch Convergence & Fus Syst Engn Dept Satellite Geoinformat Engn Sangju South Korea

Shoreline change assessment is an important task for protecting coastal properties and preserving coastal environments. This research aimed to assess the shoreline changes using the multi-temporal Landsat imagery, acquired from the east coast of South Korea during 1994 and 2014. The procedure for the shoreline change assessment consists of the following steps: (i) generating the normalized difference water index (NDWI) map from each Landsat image;(ii) extracting the shorelines from each NDWI map through the thresholding method;and (iii) assessing the shoreline changes in the various types of coasts such as the sandy, rocky and harbour coasts using the checkpoints with 1km intervals. The statistical results showed that 94% of the shorelines in the sandy coasts and 96% of the shorelines in the rocky coasts moved landward between 1994 and 2014 due to coastal erosions, while 91% of the shorelines in the harbour coasts moved seaward during the same period due to the land reclamation works. This research contributed to the assessment of the shoreline changes and the calculation of the erosion rates in the various coasts of the study area between 1994 and 2014.

关键词： SHORELINES COASTS LANDSAT satellites COASTAL ecosystem health NORMALIZED difference vegetation index thresholding algorithms KOREA (South)

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A Multidimensional Scaling Optimization and Fusion Approach For the Unsupervised Change Detection Problem in Remote Sensing Images 6

A Multidimensional Scaling Optimization and Fusion Approach ...

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6th International Conference on Image Processing Theory, Tools and Applications (IPTA)

作者： Touati, Redha Mignotte, Max Univ Montreal DIRO Montreal PQ Canada

ISBN: (纸本)9781467389105

It is generally well known that the overall performance of the most widely used types of unsupervised change detection methods, based on the luminance pixel-wise difference, is mainly relied on the quality of the so-called difference image and the accuracy of the classification method. In order to address these two issues, this work proposes to first estimate, a new and robust similarity feature map, playing the same role as the difference image, by specifying a set of constraints expressed for each pair of pixels existing in the multitemporal images. As a consequence, the proposed change detection method does not require any preprocessing step of the multitemporal images such as radiometric correction/normalization. In addition, input data can be acquired from different sensors. The quadratic complexity in the number of pixels of this new similarity feature map, between the multitemporal images, is reduced to a linear complexity procedure thanks to the FastMap-based optimization algorithm. Second, in order to achieve more robustness, changes are then identified, from this similarity feature map, by combining ( fusing) the results of different automatic thresholding algorithms. Experimental results confirm the robustness of the proposed approach.

关键词： Change detection Data fusion Multidimensional scaling Multitemporal multimodal images thresholding algorithms

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