A digital image processing system was used to non-destructively measure the full-field deformation on aluminum and wood specimens loaded in compression and bending. The measurement technique consisted of creating a random speckle pattern on the specimen surface, recording images before deformation and after deformation, and computing the relative displacements of small image subsets. Two methods for producing speckle patterns on the specimens were studied: spray paint and adhesive-backed photographic film. Baseline tests were conducted to evaluate the influence of signal noise on the measurement system. Uniform translation tests were conducted to evaluate the capability of the system for measuring finite motion. the technique was used to monitor the full-field deformation response of aluminum and wood specimens tested in bending and static compression. Moderate duration compression creep tests were conducted, on the wood specimens to investigate the suitability of the system for monitoring the creep response of materials. The results obtained from the two speckle techniques were also. compared. The results showed that for the magnification and speckle patterns tested displacement measurements smaller than 3.29x10-4 inch may be unreliable due to signal noise. / Master of Science

Two types of image processing methods capable of forming a composite image from a set of image slices which have in-focus as well as out-of-focus segments are discussed. The first type is based on space domain operations and has been discussed in the literature. The second type, to be introduced, is based on the intuitive concept that the spectral energy distribution of a focused object is biased towards lower frequencies after blurring. This approach requires digital image filtering in the spatial frequency domain. A comparison among methods of both types is made using a quantitative uÌ delity criterion. / Master of Science

The underlying piecewise continuous surface of a digital image can be estimated through robust statistical procedures. This thesis contains a systematic Monte Carlo study of M-estimation and LMS estimation for image surface approximation, an examination of the merits of postprocessing and tuning various parameters in the robust estimation procedures, and a new robust variable order facet model paradigm. Several new goodness of fit measures are introduced, and systematically compared. It is shown that the M-estimation tuning parameters are not crucial, postprocessing is cheap and well worth the cost, and the robust variable order facet model algorithm (using M-estimation, new statistical goodness of fit measures, and postprocessing) manages to retain most of the statistical efficiency of Mestimation yet displays good robustness properties, and preserves the main geometric features of an image surface: step edges, roof edges and corners. / Master of Science

A new method for the general application of quadratic spatial/spatial frequency domain filtering to imagery is presented in this dissertation. The major contribution of this research is the development of an original algorithm for approximating the inverse psuedo Wigner distribution through synthesis of an image in the spatial domain which approximates the result of filtering an original image in the DPWD domain.

No description available.

No description available.

The potential is vast for the enhancement of graphic images that are used for human interpretation and/or image display. Sensor noise, blur due to camera misfocus, relative object-camera motion, and random atmospheric turbulence may contribute to photographic image deterioration. Image enhancement and restoration methods are useful for improving the quality and for augmenting specific characteristics of an image. Often, complex filtering of the image data is required. This paper presents a technique for enhancement of images using multistage filtering techniques which take advantage of a priori knowledge as to the images' content. Algorithms are designed and implemented which enhance edges as well as gray level contrast. In addition, the source images are passed through a sequence of controllable filter stages to provide varying degrees and types of enhancements. Image enhancement techniques do not increase the inherent information content in the data, but the techniques do accentuate distinct image features which result in an improved image display. The effects of the different filters and filter stages will be analyzed with regard to image enhancement and picture quality. Numerical results and graphic image results are included in the analysis. Further applications of the techniques analyzed are discussed as well.

No description available.

No description available.

No description available.