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Adaptive synthetic aperture radar image enhancement

Adaptive synthetic aperture radar image enhancement

引用

MIPPR 2009 - Multispectral image Acquisition and processing: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Cheng, Hua Tian, Jinwen Huazhong University of Science and Technology Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies China

ISBN: (纸本)9780819478054

An adaptive SAR image enhancement method is presented for reducing the speckle noise and increasing the contrast of synthetic aperture radar (SAR) images. First, a fuzzy logic based filter, employing fuzzy edge to weight the contributions of pixel values in filter window, is used to filter the speckles. Second, the original SAR image is decomposed into lowfrequency component and high-frequency component. The fuzzy filtered image is viewed as the low-frequency component, and the contrast limited adaptive histogram equalization algorithm is used to increase its contrast. The highfrequency component is obtained by subtracting the low-frequency component from the original image, and its gain is controlled by fuzzy structural which employed to express the degree of a pixel belonging to structures. After processed one after the other, the two components are added together to form the final enhanced SAR image. Experimental results show the excellent effect of the proposed method by visual observation and numerical measurement. Many fine structures and little speckle noise can be seen from the enhanced SAR images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image enhancement

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People detection in complex scene using a cascade of boosted classifiers based on Haar-like-features

People detection in complex scene using a cascade of boosted...

引用

IEEE Symposium on Intelligent Vehicle

作者： M. Siala N. Khlifa F. Bremond K. Hamrouni Research Unit in Signal Processing Image Processing and Pattern Recognition(ENIT Tunisia) PULSAR Team (INRIA Sophia Antipolis Nice) Research Unit in Signal Processing Image Processing and Pattern Recognition(ENIT Tunisia) Tunisia

ISBN: (纸本)9781424435036

Pedestrian detection in a real scene is an interesting application for video surveillance systems. This paper presents our contribution to improve the work of Viola and Jones, originally designed to detect faces. This work uses a cascade of classifiers based on Adaboost using Haar features. It improves the learning step by including a decision tree presenting the different poses and possible occlusions. The method has been tested on real and complex sequences and has given a good detection despite occlusions and poses variation.

关键词： Layout Face detection Object detection Support vector machines Motion detection Support vector machine classification Humans Testing Robustness Detectors

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Change detection in remote sensing imagery based on multisimilarity measures fusion

Change detection in remote sensing imagery based on multisim...

引用

MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Huang, Weilin Yang, Weidong National Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

Detecting regions of change in multitemporal remote-sensing images of the same scene taken at different times is of widespread interest in recent years. In this paper, we propose a new change detection method based on a fusion of multisimilarity measures. This fusion is performed in the framework of the Dempster-Shafer evidence theory, which allows you to combine evidence from different sources and arrive at a degree of belief (represented by a belief function) that takes into account all the available evidence. The proposed algorithm is applied to airport change evaluation based on two popular Gray-textural similarity measures: grayscale difference and grayscale ratio. Experimental results confirm the effectiveness of the proposed method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Uncertainty analysis

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Ear segmentation using histogram based K-means clustering and Hough transformation under CVL dataset

Ear segmentation using histogram based K-means clustering an...

引用

MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Liu, Heng Liu, Dekai School of Information Engineering Southwest University of Science and Technology Mianyang 621010 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9780819478061

Under CVL dataset, we provide an image segmentation approach based on adaptive histogram based K-means clustering and fast Hough transformation. This work firstly analyzes the characteristics of ear images in CVL face dataset. According to the analysis, we then use adaptive histogram based K-means clustering method to threshold ear images and then roughly segment the ear parts. After ear contour extraction, with boundary determination through vertical project, Hough transformation is utilized to locate the ear contour accurately. The experimental results and comparisons with other segmentation methods show our approach is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image segmentation

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Adaptive tracking method for ground target of FLIR imaging

Adaptive tracking method for ground target of FLIR imaging

引用

MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Li, Yun Zhang, Tianxu Zuo, Zhengrong Wan, Meijun State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

An adaptive tracking method for ground target in FLIR image including centric and eccentric tracking is presented in this paper. The eccentric tracking is adopted to assist ATR or manual target acquisition by stabilizing the light axis of the seeker. The tracking adaptability detection at the start of centric tracking avoids tracking bad locked point and decreases the shift, slide and jump in the subsequent tracking. Combination of periodic template-updating based on scale variance rate and interruptive template-updating based on supervision of tracking point enhances the adaptability of tracking template. Supervision, modification of current tracking point and the combination of direct and indirect tracking increase the stability of tracking system. The multi-scale and size-variable template is adopted to fit the variable target scale. The detection and adoption of occlusion mask increase the accuracy of the tracking system. The hardware system based on multi-DSP takes a real-time parallel processing. The trial results show that this method is efficient to reduce the possibility of shift, slide, and jump in ground target tracking comparing with the traditional correlation tracking method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Target tracking

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Multivariate statistical analysis of existing image quality metrics over turbulent images

Multivariate statistical analysis of existing image quality ...

引用

2009 2nd International Congress on image and Signal processing, CISP'09

作者： Ming, Li Jie, Yang Department of Electronic Engineering Shanghai Dian Ji University Shanghai 200240 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424441310

State-of-the-art objective image quality metrics are summarized and analyzed from a new perspective. Performance comparisons of existing metrics are firstly conducted on simulated turbulence-degraded images. Then exploratory factor analysis method is used to uncover the latent relationships among existing metrics. Experimental results show that existing metrics are highly correlated to each other, and can be separated into four groups, each measuring the qualities from one aspect. Extracting the communalities of them is believed to be helpful in developing a novel metric. ©2009 IEEE.

关键词： Multivariant analysis

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Airborne target tracking algorithm against oppressive decoys in infrared imagery

Airborne target tracking algorithm against oppressive decoys...

引用

MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Sun, Xiechang Zhang, Tianxu State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

This paper presents an approach for tracking airborne target against oppressive infrared decoys. Oppressive decoy lures infrared guided missile by its high infrared radiation. Traditional tracking algorithms have degraded stability even come to tracking failure when airborne target continuously throw out many decoys. The proposed approach first determines an adaptive tracking window. The center of the tracking window is set at a predicted target position which is computed based on uniform motion model. Different strategies are applied for determination of tracking window size according to target state. The image within tracking window is segmented and multi features of candidate targets are extracted. The most similar candidate target is associated to the tracking target by using a decision function, which calculates a weighted sum of normalized feature differences between two comparable targets. Integrated intensity ratio of association target and tracking target, and target centroid are examined to estimate target state in the presence of decoys. The tracking ability and robustness of proposed approach has been validated by processing available real-world and simulated infrared image sequences containing airborne targets and oppressive decoys. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Target tracking

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Acquisition and tracking landmarks for navigation of aircraft

Acquisition and tracking landmarks for navigation of aircraf...

引用

MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Yang, Xiaoyu Zhang, Tianxu Yan, Luxin Wang, Dengwei Wang, Xiaoping State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

In this paper, we proposed a method is used to estimate an aircraft's own position in flight depending on acquisition and tracking an enlarged landmark in an image sequence. Acquisition operation is based on matching 2D template with a 2D scene of the landmark area generated by the aircraft seeker. After the landmark location is acquired, tracking the center point of the landmark maintains the slant range estimate between the sensor and the landmark which is calculated depending on data of three successive positions from the measured IMU/ GPS information. Then, we obtain the absolute position of the aircraft in the world coordinate system (WCS) with the transformation from the landmark coordinate system (LCS) into the WCS. Finally, bias errors of the Inertial Navigation are corrected for navigation of the aircraft. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Aircraft

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A novel search coding method for generic object recognition based on shared features

A novel search coding method for generic object recognition ...

引用

MIPPR 2009 - pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Zheng, Ping Sang, Nong State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

In this paper, we consider the combined problem of distinguishing classes from the background and from each other, and propose an improved framework based on the previous state-of-the-art approaches. In the process of building ECOC (Error Correcting Output Coding) matrix (also called as sharing matrix), we adopt an encoding rule of one-versus-all, and maximize Hamming distance in categories as far as possible through heuristic search in sharing-code maps (i.e., layer joint boosting). Then the final classifier is responsible for detection, and ECOC matrix for recognition. In order to make full use of the output of the final classifier and its corresponding ECOC matrix, the following measures are worth considering: Firstly, a logistic function of the output mentioned above is used for a posterior probability of each codeword. Therefore the identified class label is the one corresponding to the codeword of Maximum a posteriori (MAP). Secondly, a similarity measurement utilizing the confusion matrix is advanced to focus on the similarities between classes. Thirdly, for the purpose of adaptive adjustment in Hamming distance, we change the subsequent search coding method according to the confusion matrix until the training errors are convergent. The experimental results illustrate the effectiveness of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hamming distance

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image compression algorithm using image restoration based on wavelet analysis

Image compression algorithm using image restoration based on...

引用

MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Cheng, Zhao Zhang, Tianxu Lu, Haifeng State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

In this paper, we consider lossy image compression, which is based on wavelet theory. We introduce image restoration technology into the wavelet compression. By applying image restoration to the low-frequency component obtained by entropy decoding in decompression process, we retrieve a gained high-frequency component, which is the expression of reconstructed image texture in frequency domain. As a benchmark, the algorithm we present is compared to the traditional wavelet compression. The results of comparative experiments show that our method performs better than traditional algorithms. The PSNR in our method is elevated generally, and the reconstructed image is more texture-richer than the traditional approach without restoration. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image reconstruction

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