Target resolvability from single-tone fringe patterns of digitally spotlighted SAR image

1998 ◽  
Author(s):  
Shih I. Chou ◽  
Michael E. Pollock ◽  
Mehrdad Soumekh
Keyword(s):  
Sar Image ◽  
Single Tone ◽  
Fringe Patterns

Stress Analysis of Tire Sections

1996 ◽  
Vol 24 (4) ◽  
pp. 349-366 ◽  
Author(s):  
T-M. Wang ◽  
I. M. Daniel ◽  
K. Huang
Keyword(s):  
Finite Element ◽  
Internal Pressure ◽  
Stress Analysis ◽  
Strain Analysis ◽  
Experimental Stress ◽  
Inflation Pressure ◽  
Substantial Agreement ◽  
Finite Element Stress Analysis ◽  
Strain Components ◽  
Fringe Patterns

Abstract An experimental stress-strain analysis by means of the Moiré method was conducted in the area of the tread and belt regions of tire sections. A special loading fixture was designed to support the tire section and load it in a manner simulating service loading and allowing for Moiré measurements. The specimen was loaded by imposing a uniform fixed deflection on the tread surface and increasing the internal pressure in steps. Moiré fringe patterns were recorded and analyzed to obtain strain components at various locations of interest. Maximum strains in the range of 1–7% were determined for an effective inflation pressure of 690 kPa (100 psi). These results were in substantial agreement with results obtained by a finite element stress analysis.

Iteration Based Polarimetric SAR Image Classification

PIERS Online ◽  
2007 ◽  
Vol 3 (5) ◽  
pp. 625-628
Author(s):  
Jian Yang ◽  
Xiaoli She ◽  
Tao Xiong
Keyword(s):  
Image Classification ◽  
Sar Image ◽  
Polarimetric Sar

Survey on Fast CFAR Detection Algorithms for SAR Image Targets

2012 ◽  
Vol 38 (12) ◽  
pp. 1885 ◽  
Author(s):  
Ming-Bo ZHAO ◽  
Jun HE ◽  
Qiang FU
Keyword(s):  
Sar Image ◽  
Cfar Detection ◽  
Detection Algorithms

Speckle reduction of SAR image based on morphological Haar wavelet

2013 ◽  
Vol 32 (3) ◽  
pp. 746-748 ◽  
Author(s):  
Min LI ◽  
Zi-you ZHANG ◽  
Lin-ju LU
Keyword(s):  
Haar Wavelet ◽  
Speckle Reduction ◽  
Sar Image

FFT-Based Moving Average Maximum Likelihood Single-tone Frequency Estimation

2011 ◽  
Vol 30 (4) ◽  
pp. 831-835
Author(s):  
Yu-chun Huang ◽  
Zai-lu Huang ◽  
Ben-xiong Huang ◽  
Shu-hua Xu
Keyword(s):  
Maximum Likelihood ◽  
Frequency Estimation ◽  
Moving Average ◽  
Tone Frequency ◽  
Single Tone ◽  
Average Maximum

Segmentation of SAR Image using Fuzzy C-Means and Filters

2020 ◽  
Vol 8 (1) ◽  
pp. 84-90
Author(s):  
R. Lalchhanhima ◽  
◽  
Debdatta Kandar ◽  
R. Chawngsangpuii ◽  
Vanlalmuansangi Khenglawt ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
State Of The Art ◽  
Speckle Noise ◽  
Synthetic Aperture Radar Image ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Spatial Filters ◽  
Fuzzy C Means ◽  
Automatic Clustering ◽  
Intensity Information

Fuzzy C-Means is an unsupervised clustering algorithm for the automatic clustering of data. Synthetic Aperture Radar Image Segmentation has been a challenging task because of the presence of speckle noise. Therefore the segmentation process can not directly rely on the intensity information alone but must consider several derived features in order to get satisfactory segmentation results. In this paper, it is attempted to use the fuzzy nature of classification for the purpose of unsupervised region segmentation in which FCM is employed. Different features are obtained by filtering of the image by using different spatial filters and are selected for segmentation criteria. The segmentation performance is determined by the accuracy compared with a different state of the art techniques proposed recently.

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