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Book Wavelet Based Feature Extraction for Target Recognition and Minefield Detection

Download or read book Wavelet Based Feature Extraction for Target Recognition and Minefield Detection written by and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This project produced advances in the theory of wavelets and two-channel filter banks, and the development of new algorithms for the generation of wavelet filters and the wavelet based processing of image data, with a view towards their usefulness in image analysis for target recognition. These results include implementation of simulated annealing and Discrete Wavelet Transform algorithms, derivation of parameterizations for various useful spaces of wavelets, derivation of expressions for frequency and spatial uncertainty in wavelets, generation of wavelets optimized for different balances between spatial and frequency uncertainties, and development of wavelet transform domain denoising algorithms for feature detection algorithms. Much of the research was done on-site at the Naval Surface Warfare Center, Dahlgren, VA. Several collaborations were formed with NSWC scientists, and these produced accomplishments in addition to those in the grant proposal. Also, the P.I. presented tutorial courses and seminars to NSWC personnel. Some of the research was performed during visits to universities in South Africa, resulting in further useful and on-going collaborations. The grant supported a total of 6 graduate students (one Doctoral and 5 Masters) who performed software development and some theoretical derivations. During the period of the grant, 13 peer-reviewed papers were published (3 in journals and 10 at conferences).

Book A Wavelet based Approach to Primitive Feature Extraction Region based Segmentation and Identification for Image Information Mining

Download or read book A Wavelet based Approach to Primitive Feature Extraction Region based Segmentation and Identification for Image Information Mining written by Vijay Pravin Shah and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Content- and semantic-based interactive mining systems describe remote sensing images by means of relevant features. Region-based retrieval systems have been proposed to capture the local properties of an image. Existing systems use computationally extensive methods to extract primitive features based on color, texture (spatial gray level dependency - SGLD matrices), and shape from the segmented homogenous region. The use of wavelet transform techniques has recently gained momentum in multimedia image archives to expedite the retrieval process. However, the current semantic-enabled framework for the geospatial data uses computationally extensive methods for feature extraction and image segmentation. Hence, this dissertation presents the use of a wavelet-based feature extraction in a semantics-enabled framework to expedite the knowledge discovery in geospatial data archives. Geospatial data has different characteristics than multimedia images and poses more challenges. The experimental assumptions, such as the selection of the wavelet decomposition level and mother wavelet used for multimedia data archives, might not prove to be efficient for the retrieval of geospatial data. Discrete wavelet transforms (DWT) introduce aliasing effects due to subband decimation at a certain decomposition level. This dissertation addresses the issue of selecting a suitable wavelet decomposition level, and a systematic selection process is developed for image segmentation. To validate the applicability of this method, a synthetic image is generated to assess the performance qualitatively and quantitatively. In addition, results for a Landsat7 ETM+ imagery archive are illustrated, and the F-measure is used to assess the feasibility of this method for retrieval of different classes. This dissertation also introduces a new feature set obtained by coalescing wavelet and independent component analysis for image information mining. Feature-level fusion is performed to include the missing high detail information from the panchromatic image. Results show that the presented feature set is computationally less expensive and more efficient in capturing the spectral and spatial texture information when compared to traditional approaches. After extensive experimentation with different types of mother wavelets, it can be concluded that reverse Biorthogonal wavelets of shorter length and the simple Haar filter provided better results for the image information mining from the database used in this study.

Book A WAVELET BASED APPROACH TO PRIMITIVE FEATURE EXTRACTION REGION BASED SEGMENTATION AND IDENTIFICATION FOR IMAGE INFORMATION MINING

Download or read book A WAVELET BASED APPROACH TO PRIMITIVE FEATURE EXTRACTION REGION BASED SEGMENTATION AND IDENTIFICATION FOR IMAGE INFORMATION MINING written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Content- and semantic-based interactive mining systems describe remote sensing images by means of relevant features. Region-based retrieval systems have been proposed to capture the local properties of an image. Existing systems use computationally extensive methods to extract primitive features based on color, texture (spatial gray level dependency - SGLD matrices), and shape from the segmented homogenous region. The use of wavelet transform techniques has recently gained momentum in multimedia image archives to expedite the retrieval process. However, the current semantic-enabled framework for the geospatial data uses computationally extensive methods for feature extraction and image segmentation. Hence, this dissertation presents the use of a wavelet-based feature extraction in a semantics-enabled framework to expedite the knowledge discovery in geospatial data archives. Geospatial data has different characteristics than multimedia images and poses more challenges. The experimental assumptions, such as the selection of the wavelet decomposition level and mother wavelet used for multimedia data archives, might not prove to be efficient for the retrieval of geospatial data. Discrete wavelet transforms (DWT) introduce aliasing effects due to subband decimation at a certain decomposition level. This dissertation addresses the issue of selecting a suitable wavelet decomposition level, and a systematic selection process is developed for image segmentation. To validate the applicability of this method, a synthetic image is generated to assess the performance qualitatively and quantitatively. In addition, results for a Landsat7 ETM+ imagery archive are illustrated, and the F-measure is used to assess the feasibility of this method for retrieval of different classes. This dissertation also introduces a new feature set obtained by coalescing wavelet and independent component analysis for image information mining. Feature-level fusion is performed to include the missing hig.

Book Wavelet Based Signal and Image Processing for Target Recognition

Download or read book Wavelet Based Signal and Image Processing for Target Recognition written by and published by . This book was released on 2002 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the initial year of the project new wavelet based signal and image processing algorithms were developed, specifically directed towards usefulness in target recognition applications. Classical spatial and frequency domain image processing algorithms were generalized to process discrete wavelet transform (DWT) data. Results include adaptation of classical filtering, smoothing and interpolation techniques to DWT. From 2003 the research direction changed, in keeping with changes in the direction of ONR's Probability and Statistics Program. A sabbatical leave was devoted to broadening the P.I.'s expertise in aspects of Pattern Recognition. Research was also done on-site at the Naval Surface Warfare Center, Dahlgren, Virginia, where collaborations were formed with NSWC scientists. These resulted, inter alia, in the development of a new tracking algorithm for laser guided weapons. While at NSWC, the P.I. presented tutorial courses and seminars to NSWC scientists. The grant supported 4 graduate students who performed software development and theoretical derivations. During the grant period, 8 peer-reviewed papers were published.

Book Proceedings of International Joint Conference on Advances in Computational Intelligence

Download or read book Proceedings of International Joint Conference on Advances in Computational Intelligence written by Mohammad Shorif Uddin and published by Springer Nature. This book was released on 2022-05-18 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding research papers presented at the 5th International Joint Conference on Advances in Computational Intelligence (IJCACI 2021), held online during October 23–24, 2021. IJCACI 2021 is jointly organized by Jahangirnagar University (JU), Bangladesh, and South Asian University (SAU), India. The book presents the novel contributions in areas of computational intelligence and it serves as a reference material for advance research. The topics covered are collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

Book Automatic Target Recognition Using Wavelet Based Vector Quantization

Download or read book Automatic Target Recognition Using Wavelet Based Vector Quantization written by Lipchen Chan and published by . This book was released on 1997 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: An automatic target recognition classifier is described that uses a set of dedicated vector quantizers (VQs) in the wavelet domain. The background pixels in each input image are properly clipped out by a set of aspect windows. The extracted target area for each aspect window is then enlarged to a fixed size, after which a wavelet decomposition is used to split this region into several subbands. A dedicated VQ codebook is then generated for each subband of a particular target class at a specific range of aspects. Thus, each codebook consists of a set of feature templates that are iteratively adapted to represent a particular subband of a given target class at a specific range of aspects. These templates are then further trained by a modified learning vector quantization (LVQ) algorithm that enhances their discriminatory characteristics. Finally, a path selector was designed to speed up the recognition process at the expense of a tolerable degradation in the recognition rate.

Book Robust Feature Detection Using 2D Wavelet Transform Under Low Light Environment

Download or read book Robust Feature Detection Using 2D Wavelet Transform Under Low Light Environment written by Youngouk Kim and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper presents a local feature detection method for vSLAM-based self-localization of mobile robots. Extraction of strong feature points enables accurate self-localization under various conditions. We first proposed NAST pre-processing filter to enhance low light-level input images. The SIFT algorithm was modified by adopting wavelet transform instead of Gaussian pyramid construction. The wavelet-based pyramid outperformed the original SIFT in the sense of processing time and quality of extracted keypoints. A more efficient local feature detector and a compensation scheme of noise due to the low contrast images are also proposed. The proposed scene recognition method is robust against scale, rotation, and noise in the local feature space.

Book Wavelet Coefficient Based Feature Extraction

Download or read book Wavelet Coefficient Based Feature Extraction written by Gregory A. Mesolella and published by . This book was released on 1994 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Feature Extraction for Robust Automatic Target Recognition

Download or read book Feature Extraction for Robust Automatic Target Recognition written by and published by . This book was released on 2006 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Minefield Identification in Clutter Using Wavelet Transform

Download or read book Minefield Identification in Clutter Using Wavelet Transform written by Xiao Liu and published by . This book was released on 1998 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Detection Technologies for Mines and Minelike Targets

Download or read book Detection Technologies for Mines and Minelike Targets written by Abinash C. Dubey and published by SPIE-International Society for Optical Engineering. This book was released on 1995 with total page 1066 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Image Feature Extraction Via the Wavelet Transform and Quadrature Mirror Filters

Download or read book Image Feature Extraction Via the Wavelet Transform and Quadrature Mirror Filters written by Winston Kafui Awadzi and published by . This book was released on 1994 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: