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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.
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 …
Video Compression Using Wavelets And Hierarchical Motion Estimation, Andrew Peter Byrne
Video Compression Using Wavelets And Hierarchical Motion Estimation, Andrew Peter Byrne
Theses : Honours
This thesis investigates the benefits and the significant compression that can be obtained from data that has been decomposed using a wavelet transform. A video compression algorithm was developed that employs the wavelet transform and a hierarchical motion estimation algorithm which itself utilises benefits of the wavelet transform. Using MATLAB, a popular software tool for matrix based computation and analysis, several functions were developed which together formed the video compression algorithm. A variety of tests were conducted on a sample video sequence to ascertain the strengths and weaknesses of the techniques employed. The results, although not the same as the …
Vhdl Design And Simulation For Embedded Zerotree Wavelet Quantisation, Hung Huynh
Vhdl Design And Simulation For Embedded Zerotree Wavelet Quantisation, Hung Huynh
Theses : Honours
This thesis discusses a highly effective still image compression algorithm – The Embedded Zerotree Wavelets coding technique, as it is called. This technique is simple but achieves a remarkable result. The image is wavelet-transformed, symbolically coded and successive quantised, therefore the compression and transmission/storage saving can be achieved by utilising the structure of zerotree. The algorithm was first proposed by Jerome M. Shapiro in 1993, however to minimise the memory usage and speeding up the EZW processor, a Depth First Search method is used to transverse across the image rather than Breadth First Search method as initially discussed in Shapiro's …
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 …