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Full-Text Articles in Signal Processing
Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration, Daniel L. Ward
Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration, Daniel L. Ward
Theses and Dissertations
The limited resolution of video imagery taken by aircraft, over geographical areas of interest, hinders the accurate extraction of useful information. The frame resolution of the video is determined by the camera that created it. Information exists about the camera which can be used to increase frame resolution beyond the resolution capability of the camera. This is achieved by a process called super-resolution, which uses multiple low-resolution video frames to create one high-resolution image.
Feature Guided Image Registration Applied To Phase And Wavelet-Base Optic Flow, Kate R. Duffy
Feature Guided Image Registration Applied To Phase And Wavelet-Base Optic Flow, Kate R. Duffy
Theses and Dissertations
Optic Flow algorithms are useful in problems such as computers vision, navigational systems, and robotics. However, current algorithms are computationally expensive or lack the accuracy to be effective compared with traditionally navigation systems. Recently, lower accuracy inertial navigation systems (INS) based on Microelectromechanical systems (MEMS) technology have been proposed to replace more accurate traditional navigation systems.
Wavelet Domain Communication System (Wdcs): Packet-Based Wavelet Spectral Estimation And M-Ary Signaling, Marion Jay F. Lee
Wavelet Domain Communication System (Wdcs): Packet-Based Wavelet Spectral Estimation And M-Ary Signaling, Marion Jay F. Lee
Theses and Dissertations
A recently proposed Wavelet Domain Communication System (WDCS) using transform domain processing demonstrated excellent interference avoidance capability under adverse environmental conditions. This work extends previous results by: 1) incorporating a wavelet packet decomposition technique, 2) demonstrating M-Ary signaling capability, and 3) providing increased adaptivity over a larger class of interference signals. The newly proposed packet-based WDCS is modeled and its performance characterized using MATLAB®. In addition, the WDCS response to two scenarios simulating Doppler effects and physical separation of transceivers are obtained. The fundamental metric for analysis and performance evaluation is bit error rate (Pb). Relative to …
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Theses and Dissertations
The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …
Image Registration Using Redundant Wavelet Transforms, Richard K. Brown
Image Registration Using Redundant Wavelet Transforms, Richard K. Brown
Theses and Dissertations
Imagery is collected much faster and in significantly greater quantities today compared to a few years ago. Accurate registration of this imagery is vital for comparing the similarities and differences between multiple images. Since human analysis is tedious and error prone for large data sets, we require an automatic, efficient, robust, and accurate method to register images. Wavelet transforms have proven useful for a variety of signal and image processing tasks, including image registration. In our research, we present a fundamentally new wavelet-based registration algorithm utilizing redundant transforms and a masking process to suppress the adverse effects of noise and …
Adaptive And Fixed Wavelet Features For Narrowband Signal Classification, Anthony J. Pohl
Adaptive And Fixed Wavelet Features For Narrowband Signal Classification, Anthony J. Pohl
Theses and Dissertations
The application of the multiresolution analysis developed by Mallat to signal classification by Pati and Krishnaprasad and Szu, et al, is further explored in this thesis. Several different wavelet based feature extraction and classification systems are developed and implemented. Methods which rely on the traditional dyadic wavelet decomposition and on the adaptive wavelet representation are presented. Each of the classification systems is implemented for a labeled data set of narrowband signals. Finally, classification results on the full data set and on low frequency Fourier coefficients are provided as baseline comparisons for our work.
Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk
Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk
Theses and Dissertations
A comparative study of texture measures for the classification of breast tissue is presented. The texture features investigated include Angular Second Moments, Power Spectrum Analysis and a novel feature, Laws Energy Ratios. The texture study was accomplished as part of the development of a Model Based Vision (MBV) system for the automatic detection of microcalcifications. An overview of the Microcalcification Detection System is presented, which applies image differencing techniques, feature selection methods, and neural networks for locating microcalcification clusters in mammograms. The Power Spectrum Analysis feature set had the best overall performance with an 83% Probability of Detection and an …
Multipoint Multirate Signal Processing, Roger L. Claypoole Jr.
Multipoint Multirate Signal Processing, Roger L. Claypoole Jr.
Theses and Dissertations
This thesis provides a fundamentally new, systematic study of multipoint multirate signal processing systems. The multipoint multirate operators are analyzed via equivalent circuits comprised entirely of conventional multirate operators. Interconnections of the operators are demonstrated, and the multipoint noble identities are derived. The multipoint polyphase representation is presented, and the M channel multipoint multirate system with vector length N is presented as an MN channel multipoint polyphase system. The conditions sufficient for perfect reconstruction in the multipoint multirate system are derived. These conditions constrain the multipoint filter banks to be composed of comb filters generated from paraunitary sets of conventional …
Noise Reduction For Speech Enhancement Using Non-Linear Wavelet Processing, Hassan Dehmani
Noise Reduction For Speech Enhancement Using Non-Linear Wavelet Processing, Hassan Dehmani
Theses and Dissertations
The problem of speech enhancement presents many obstacles in the speech processing field. This thesis develops several speech de-noising systems that can be used in the time, fourier, and wavelet domains. We present two thresholding techniques soft and hard. The application of these thresholding techniques to noisy speech data is discussed. The combination of both wavelets and the Fourier domains with noisy phase restoration proves to yield the best results in terms of intelligibility. Informal listening tests were conducted in order to compare the effects and differences between the speech de-noising systems.
Filtering, Coding, And Compression With Malvar Wavelets, Stephen R. Hall
Filtering, Coding, And Compression With Malvar Wavelets, Stephen R. Hall
Theses and Dissertations
This thesis develops and evaluates a number of new concepts and tools for the analysis of signals using Malvar wavelets lapped orthogonal transforms . Windowing, often employed as a spectral estimation technique, can result in irreparable distortions in the transformed signal. By utilizing the Malvar wavelet, any signal distortion resulting from the transformation can be eliminated or cancelled during reconstruction. This is accomplished by placing conditions on the window and the basis function and then incorporating the window into the orthonormal representation. Paradigms for both a complex-valued and a real-valued Malvar wavelet are summarized. I-lie algorithms for the wavelets were …
Color Image Segmentation, Kimberley A. Mccrae
Color Image Segmentation, Kimberley A. Mccrae
Theses and Dissertations
The most difficult stage of automated target recognition ATR is segmentation. Current AFIT segmentation problems include faces and tactical targets previous efforts to segment these objects have used intensity and motion cues. This thesis develops a color preprocessing scheme to be used with the other segmentation techniques. A neural network is trained to identify the color of a desired object, eliminating all but that color from the scene. Gabor correlations and 2D wavelet transformations will be performed on stationary images and 3D wavelet transforms on multispectral data will incorporate color and motion detection into the machine visual system. The thesis …