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Articles 31 - 43 of 43
Full-Text Articles in Signal Processing
Fast Compression Of Imagery With High Frequency Content, D. Scott Anderson
Fast Compression Of Imagery With High Frequency Content, D. Scott Anderson
Theses and Dissertations
Image compression is an active area due to the many applications involving electronic media. Much research has been focused on image quality versus bit rate and/or algorithm speed. Here, we seek an effective image coder with a weighted constraint on speed. However, the compression must not taint the quality of impulsive features on the image. Moreover, the camera is operated in a mode that creates a dominant fixed pattern noise across the image array, degrading visual quality and disrupting compression performance. We propose a method that efficiently compresses such an image. We begin by characterizing and removing the fixed pattern …
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 …
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
Theses and Dissertations
Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This thesis evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentors. This objective comparison uses a multi-metric a approach with a set of …
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …
Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan
Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan
Electrical & Computer Engineering Theses & Dissertations
Motivated by the fact that human speech perception is a bimodal process (auditory and visual), several researchers have designed and implemented automatic speech recognition (ASR) systems consisting of both audio and visual subsystems, and shown improved performance relative to traditional purely auditory systems. Several visual speech reading approaches have used deformable templates to model the shape of a speaker's lips. Deformable templates are models of image objects, which can be deformed by adjusting a set of parameters to match the object in some optimal way, as defined by a cost function. Using a single deformable lip model has disadvantages such …
The Role Of Frame Selection And Bispectrum Phase Reconstruction For Speckle Imaging Through Atmospheric Turbulence, Elizabeth A. Harpold
The Role Of Frame Selection And Bispectrum Phase Reconstruction For Speckle Imaging Through Atmospheric Turbulence, Elizabeth A. Harpold
Theses and Dissertations
Frame selection using quality sharpness metrics have been shown in previous AFIT theses, to be effective in improving the final product of images obtained using adaptive optics. This thesis extends this idea to noncompensated speckle image data. Speckle image reconstruction is simulated with and without frame selection. Speckle images require the processing of hundreds of data frames. Frame selection is a method of reducing the amount of data required to reconstruct the image. A collection of short exposure image data frames of a single object are sorted based on sharpness metrics. Only the highest quality frames are retained and processed …
Perceptual Based Image Fusion With Applications To Hyperspectral Image Data, Terry A. Wilson
Perceptual Based Image Fusion With Applications To Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Development of new imaging sensors has created a need for image processing techniques that can fuse images from different sensors or multiple images produced by the same sensor. The methods presented here focus on combining image data from the Airborne Visual and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor into a single or smaller subset of images while maintaining the visual information necessary for human analysis. Three hierarchical multi-resolution image fusion techniques are implemented and tested using the AVIRIS image data and test images that contain various levels of correlated or uncorrelated noise. Two of the algorithms are published fusion methods …
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 …
A Radiosity Approach To Realistic Image Synthesis, Richard L. Remington
A Radiosity Approach To Realistic Image Synthesis, Richard L. Remington
Theses and Dissertations
The Air Force Institute of Technology (AFIT) has not had the capability to generate photorealistic images. This thesis is a research effort to implement such a system at AFIT, and to apply knowledge from the particle transport community to this problem. Investigation into various techniques for generating photorealistic images led to the conclusion that the radiosity method would serve as the foundation for development. This is because of the increased accuracy of the diffuse reflections with the radiosity method and the fact that the images produced with radiosity axe view-independent. Two distinct tools to generate photorealistic images axe described. The …
Optical Image Segmentation Using Wavelet Correlation, Steven D. Pinski
Optical Image Segmentation Using Wavelet Correlation, Steven D. Pinski
Theses and Dissertations
This research introduces an optical method of segmenting potential targets using wavelet analysis. Implementation of an optical Harr wavelet is fulfilled using a magneto-optic spatial light modulator (MOSLM). Two methods of controlling wavelet dilation are explored: (1) spatial filtering of a ternary modulated MOSLM; (2) a single aperture positioned in front of a binary modulated MOSLM. Segmentation is performed through Vander Lugt correlation of a binarized image with a binarized optical wavelet. Three different image binarization methods are investigated for use in the correlation scheme: (1) average pixel value over an entire scene; (2) localized 4 x 4 pixel average …
Image Segmentation Using Affine Wavelets, Steven E. Smiley
Image Segmentation Using Affine Wavelets, Steven E. Smiley
Theses and Dissertations
This thesis discusses the use of the multiresolution representation and Radial Basis Function (RBF) neural networks to segment both FLIR and SAR imagery. The multiresolution approximation coefficients are used as features into the RBF network which learns to distinguish between different cultural and natural regions or objects. The wavelets used are Mallat's spline wavelet and Daubechies' compactly supported wavelets. Additionally, this thesis provides an explanation of wavelets in a tutorial manner. It introduces wavelet theory and discusses two different approaches to generating the multiresolution or wavelet representation.
Fractal Geometry Segmentation Of High Resolution Polarimetric Synthetic Aperture Radar Data, Joseph L. Brickey
Fractal Geometry Segmentation Of High Resolution Polarimetric Synthetic Aperture Radar Data, Joseph L. Brickey
Theses and Dissertations
This thesis investigated the potential of fractal dimension estimation for segmenting high resolution polarimetric synthetic aperture radar. The data used during this research were collected with the Advanced Detection Technology Sensor (ADTS) developed by Massachusetts Institute of Technology Lincoln Laboratory with Defense Advanced Research Projects Agency funding. ADTS is a fully polarimetric calibrated 35 GHz SAR with one foot impulse response. A method of applying the correlation dimension algorithm developed by Grassberger and Procaccia for estimating the dimension of time series data was implemented to estimate the correlation dimension of polarimetric SAR data. A threshold sensitivity study was performed to …