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Shift-Invariant Image Reconstruction of Speckle-Degraded Images Using Bispectrum Estimation
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
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Coherent speckle noise as a multiplicative noise process that has a negative exponential probability density function. Using a homomorphic transformation, this speckle noise is converted to a signal-independent, additive process. The speckled images are randomly jittered from frame-to-frame against a uniform background to simulate image motion andor platform jitter. Multiple images are logarithmically transformed and ensemble averaged in the bispectral domain. The bispectrum ignores this image motion so no blurring results from the ensemble averaging. Object Fourier magnitude and phase information are also retained in the bispectrum so that the resultant image can be uniquely reconstructed. This value is then exponentiated to complete the image reconstruction process. Since speckle masks the resolution of details in the noisy image and effectively destroys the object structure within the image, it is seen that image reconstruction using bispectrum estimation results in images that regain their object structure. Both one-dimensional and two- dimensional images were tested using separate bispectral signal reconstruction algorithms for each. RH
APPROVED FOR PUBLIC RELEASE