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Multi-resolution image fusion using multistage guided filter

Multi-resolution image fusion using multistage guided filter

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National conference on Computer Vision, pattern recognition, image processing and Graphics (NCVPRIPG)

作者： Sharad Joshi Kishor P. Upla Manjunath V. Joshi S. V. National Institute of Technology Surat Gujarat India Dhirubhai Ambani Inst. of Information and Comm. Technology Gahdhinagar Gujarat India

In this paper, we propose a multi-resolution image fusion approach based on multistage guided filter (MGF). Given the high spatial resolution panchromatic (Pan) and high spectral resolution multi-spectral (MS) images, the multi-resolution image fusion algorithm obtains a single fused image having both the high spectral and the high spatial resolutions. Here, we extract the missing high frequency details of MS image by using multistage guided filter. The detail extraction process exploits the relationship between the Pan and MS images by utilizing one of them as a guidance image and extracting details from the other. This way the spatial distortion of MS image is reduced by consistently combining the details obtained using both types of images. The final fused image is obtained by adding the extracted high frequency details to corresponding MS image. The results of the proposed algorithm are compared with the commonly used traditional methods as well as with a recently proposed method using Quickbird, Ikonos-2 and Worldview-2 satellite images. The quantitative assessment is evaluated using the conventional measures as well as using a relatively new index i.e., quality with no reference (QNR) which does not require a reference image. The results and measures clearly show that there is significant improvement in the quality of the fused image using the proposed approach.

关键词： Satellites Satellite broadcasting remote sensing image fusion Spatial resolution Wavelet transforms

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Survey of image segmentation algorithms on ultrasound medical images

Survey of image segmentation algorithms on ultrasound medica...

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International conference on pattern recognition, Informatics and Medical Engineering

作者： S. Sridevi M. Sundaresan Department of Information Technology Bharathiar University Coimbatore India

Visual information plays an important role in almost all areas our life. Nowadays, much of this information is represented and processed digitally. image processing is ubiquitous, with the applications ranging from Television (TV) to Computed Tomography, from Photography to Printing, from Robotics to remote sensing and medical applications. Ultrasound is one of the techniques for medical application. It is used for clinical usage. The most important technologies include transducers, beam forming, contrast agents, pulse compression techniques for measuring blood flow and three-dimensional imaging. Ultrasound imaging provides valuable imaging modality to provide the following functionalities as ease of use, low cost, safe, non invasive and fast examination. Ultrasound imaging system provides effective way for examining the various tissues of human body including thyroid, breast, abdominal organs, heart, muscles, tendons, arteries and veins. This paper aims to present on current segmentation algorithms used for medical images. Each and every type of algorithm is discussed as well as their main application fields identified. Experiments that apply the algorithms to segment ultrasound images are presented to further evaluate their behaviour.

关键词： image segmentation Ultrasonic imaging Doppler effect image edge detection Level set Biomedical imaging

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Pan-sharpening based on Non-subsampled Contourlet Transform detail extraction

Pan-sharpening based on Non-subsampled Contourlet Transform ...

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National conference on Computer Vision, pattern recognition, image processing and Graphics (NCVPRIPG)

作者： Kishor P. Upla Prakash P. Gajjar Manjunath V. Joshi S. V. National Institute of Technology Surat Gujarat India Govt. Polytechnic Ahmedabad Gujarat India Dhirubhai Ambani Inst. of Infor. & Comm. Tech Gahdhinagar Gujarat India

In this paper, we propose a new pan-sharpening method using Non-subsampled Contourlet Transform. The panchromatic (Pan) and multi-spectral (MS) images provided by many satellites have high spatial and high spectral resolutions, respectively. The pan-sharpened image which has high spatial and spectral resolutions is obtained by using these images. Since the NSCT is shift invariant and it has better directional decomposition capability compared to contourlet transform, we use it to extract high frequency information from the available Pan image. First, two level NSCT decomposition is performed on the Pan image which has high spatial resolution. The required high frequency details are obtained by using the coarser subband available after the two level NSCT decomposition of the Pan image. The coarser sub-band is subtracted from the original Pan image to obtain these details. These extracted details are then added to MS image such that the original spectral signature is preserved in the final fused image. The experiments have been conducted on images captured from different satellite sensors such as IKonos-2, Worlview-2 and Quickbird. The traditional quantitative measures along with quality with no reference (QNR) index are evaluated to check the potential of the proposed method. The proposed approach performs better compared to the recently proposed state of the art methods such as additive wavelet luminance proportional (AWLP) method and context based decision (CBD) method.

关键词： Spatial resolution Transforms remote sensing Satellites Sensors image sensors

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Descriptor Correlation Analysis for remote sensing image Multi-Scale Classification

Descriptor Correlation Analysis for Remote Sensing Image Mul...

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21st International conference on pattern recognition (ICPR)

作者： dos Santos, J. A. Faria, F. A. Torres, R. da S. Rocha, A. Gosselin, P-H. Philipp-Foliguet, S. Falcao, A. Univ Estadual Campinas Inst Comp RECOD Lab Campinas SP Brazil Univ Cergy Pontoise CNRS ENSES ETIS Cergy France

ISBN: (纸本)9784990644109;9781467322164

This paper addresses the problem of remote sensing image multi-scale classification by: (i) showing that using multiple scales does improve classification results, but not all scales have the same importance;(ii) showing that image descriptors do not offer the same contribution at all scales, as commonly thought, and some of them are very correlated;(iii) introducing a simple approach to automatically select segmentation scales, descriptors, and classifiers based on correlation and accuracy analysis.

关键词： remote sensing images multi-scale Descriptors accuracy analysis Dermal denticles BALANCES Classifiers Subject Headings Correlation analysis

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Highly Accurate Estimation of Sub-pixel Motion Using Phase Correlation

Highly Accurate Estimation of Sub-pixel Motion Using Phase C...

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Chinese conference on pattern recognition

作者： Yu, Yinghuai Wang, Jinrong Guangdong Ocean Univ Coll Informat Zhanjiang 524088 Peoples R China Guangdong Ocean Univ Lab Ocean Remote Sensing & Informat Technol Zhanjiang 524088 Peoples R China Guizhou Univ Coll Sci Guiyang 550025 Peoples R China

ISBN: (纸本)9783642335051

Motion estimation is one of the basic problems in digital video processing;it is significant in the applications of video image compression, super-resolution reconstruction, mosaic, and target detection, and so on. In the base of discussing usual phase correlation algorithm, we present an improved algorithm for the problem of highly accurate sub-pixel motion estimation, which introduces zero-padding for computing the initial estimate at sub-pixel level, and also adopts the method of paraboloid fitting phase correlation for refining the initial estimate. Experimental results show that the proposed algorithm can not only achieve good robustness to the influence of noise, but can also improve the accuracy of motion estimation significantly.

关键词： Sub-pixel motion estimation phase correlation zero-padding paraboloid fitting

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Multi-Feature Model Analysis-Based Target Identification for remote sensing image

Multi-Feature Model Analysis-Based Target Identification for...

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2012 IEEE 11th International conference on Signal processing(ICSP 2012)

作者： Lin Qi Jinfeng Yang Yuchun Wen Pengfei Ma Chenghua Xu Hui Hao Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Information Creation Engineering Center Institute of ElectronicsChinese Academy of Sciences The Administration Center of Urban-Rural Planning Ministry of Housing and Urban-Rural Development

ISBN: (纸本)9781467321969

Recently, target identification has become a key topic due to the richness of nature resources contained in high-resolution remote sensing image. Many algorithms have been proposed in this aspect. In order to reduce algorithmic complexity and shorten computing cost, a multi-feature analysis model is proposed to identify targets in remote sensing images. The originality of the method includes two aspects. （1） City planning diagram, which is a vector file in the term of polygons of indispensable attributes, is used for image partition. （2） Multiple features are modeled, and then an identification rule is developed based on the model and minimum distance classification. Experimental results show that the proposed method is reliable in performing target identification.

关键词： target identification multi-feature city planning diagram model file

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Using GLIDER for Knowledge Discovery in Climate Science to Visualize, Analyze and Mine Satellite imagery

Using GLIDER for Knowledge Discovery in Climate Science to V...

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25th ACM/IEEE International conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Graves, Sara Ramachandran, Rahul Berendes, Todd Univ Alabama Informat Technol & Syst Ctr Huntsville AL 35899 USA

ISBN: (纸本)9780769549569;9781467362184

Satellite remote sensing provides an essential source of information for monitoring the earth's atmosphere and climate. Thematic information derived from satellite imagery is applicable to a wide variety of applications at local, regional and global scales. Extracting thematic information using satellite imagery is a non-trivial task that usually requires preprocessing data by applying operations for radiometric and geometric corrections. Analysts need the ability to interactively apply different image enhancement operations to digitally enhance imagery, in order to identify subtle information that might be otherwise missed. Advanced algorithms are needed to allow users to analyze imagery and extract thematic information without having to alter the original data through geographic projections. The Globally Leveraged Integrated Data Explorer for Research (GLIDER) is an easy to use tool for visualization, analysis and mining of satellite imagery. Users can visualize and analyze satellite imagery in its native sensor view, which is an important capability since geographic projections can result in loss of information. A full suite of image processing, pattern recognition and data mining algorithms is provided for image enhancement and analysis. Analysis results and imagery can then be displayed simultaneously and compared using a 3-D globe display that supports image overlays and web map service (WMS) layers. Examples will be shown to illustrate how GLIDER provides views and tools to facilitate knowledge discovery from satellite imagery.

关键词： Geoscience and remote sensing Data Mining Supervised Learning

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Unscented particle filter in road extraction from high resoltuion satellite images

Unscented particle filter in road extraction from high resol...

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International conference on Recent Trends in Information Technology, ICRTIT 2012

作者： Subash, Jenita Department of Electronics and Communication Engineering Cambridge Institute of Technology K.R Puram Bangalore India

ISBN: (纸本)9781467316019

A typical way to update map is to compare recent satellite images with existing map data, detect new roads and add them as cartographic entities to the road layer. At present image processing and pattern recognition are not robust enough to automate the image interpretation system feasible. For this reason we have to develop image interpretation systems that rely on human guidance. More importantly road maps require final checking by a human due to the legal implementations of error. Our proposed technique is applied to Indian remote sensing and IKONOS satellite images using Unscented Particle Filter. Unscented particle filter is used for tracing the median axis of the single road segment. The Extended Kalman Filter is probably the most widely used estimation algorithm for road tracking. However, more than 35 years of experience in the estimation community has shown that is difficult to implement and is difficult to tune. To overcome this limitation, Unscented particle filter is introduced in road tracking which is more accurate, easier to implement, and uses the same order of calculations as linearization. The principles and algorithm of unscented kalman filter and unscented particle filter were also discussed. The core of our system is based on profile matching. Unscented Particle filter traces the road beyond obstacles and tries to find the continuation of the road finding all road branches initializing at the road junction. The completeness and correctness of road tracking from the Indian remote sensing and IKONOS images were also compared. © 2012 IEEE.

关键词： image analysis

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Edge preserving image fusion based on contourlet transform

Edge preserving image fusion based on contourlet transform

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5th International conference on image and Signal processing, ICISP 2012

作者： Khare, Ashish Srivastava, Richa Singh, Rajiv Department of Electronics and Communication University of Allahabad Allahabad India

ISBN: (纸本)9783642312533

image fusion is an emerging area of research having a number of applications in medical imaging, remote sensing, satellite imaging, target tracking, concealed weapon detection and biometrics. In the present work, we have proposed a new edge preserving image fusion method based on contourlet transform. As contourlet transform has high directionality and anisotropy, it gives better image representation than wavelet transforms. Also contourlet transform represents salient features of images such as edges, curves and contours in better way. So it is well suited for image fusion. We have performed experiments on several image data sets and results are shown for two datasets of multifocus images and one dataset of medical images. On the basis of experimental results, it was found that performance of proposed fusion method is better than wavelet transform (Discrete wavelet transform and Stationary wavelet transform) based image fusion methods. We have verified the goodness of the proposed fusion algorithm by well known image fusion measures (entropy, standard deviation, mutual information (MI) and ). The fusion evaluation parameters also imply that the proposed edge preserving image fusion method is better than wavelet transform (Discrete wavelet transform and Stationary wavelet transform) based image fusion methods. © 2012 Springer-Verlag.

关键词： Contourlet transform

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1st International conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012

1st International Conference on Advanced Machine Learning Te...

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ISBN: (纸本)9783642353253

The proceedings contain 59 papers. The special focus in this conference is on Rough Sets and Applications, Machine Learning in pattern recognition and image processing, Machine Learning in Multimedia Computing, Bioinformatics and Cheminformatics, Data Classification and Clustering, Cloud Computing and Recommender Systems, Case-Based Reasoning and Data processing, Authentication, Digital Forensics and Plagiarism Detection. The topics include: Rough sets-based machine learning over non-deterministic data;learning a table from a table with non-deterministic information;parameterised fuzzy Petri nets for approximate reasoning in decision support systems;rough sets-based rules generation approach;automatic color image segmentation based on illumination invariant and superpixelization;wavelet based statistical adapted local binary patterns for recognizing avatar faces;solving avatar captchas automatically;comparative analysis of image fusion techniques in remote sensing;density based fuzzy thresholding for image segmentation;subjectivity and sentiment analysis of Arabic;support vector machine approach for detecting events in video streams;study of feature categories for musical instrument recognition;a genetic-CBR approach for cross-document relationship identification;improved action recognition using an efficient boosting method;towards smart Egypt -the role of large scale WSNs;language for writing descriptors of outline shape of molecules;web service based approach for viral hepatitis ontology sharing and diagnosing;sampleboost for capsule endoscopy categorization and abnormality detection;advanced parallel genetic algorithm with gene matrix for global optimization;semi-possibilistic biclustering applied to discrete and continuous data;a comparative study of localization algorithms in WSNs;test cases automatic generator (TCAG);support vector machines with weighted powered kernels for data classification;an enhanced cloud-based view materialization approach for peer-to-

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