Three-dimensional microscopy by computational deconvolution methods requires accurate knowledge of the point spread function (PSF) that characterizes the microscope. Experimental PSF’s can only be measured over small regions about focus because the small objects necessary for PSF measurement are dim. Theoretical computation of the PSF requires accurate knowledge of all the experimental setup pa...

Deconvolution refers to the problem of estimating the unknown input to an LTI system when the output signal and system response are known. In practice, the available output signal is also noisy. For some systems, the deconvolution problem is quite straight forward; however, for systems that are non-invertible or nearly non-invertible (e.g. narrow-band or with frequency response nulls), the prob...

OF THESIS Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science Optical Science and Engineering The University of New Mexico Albuquerque, New Mexico May, 2007

We present an automatic focus area estimation method, working with a single image without a priori information about the image, the camera, or the scene. It produces relative focus maps by localized blind deconvolution and a new residual error-based classification. Evaluation and comparison is performed and applicability is shown through image indexing.

Since its introduction in 1983, deconvolution microscopy has become a key image-processing tool for visualizing the cellular structures of fixed and living specimens in three dimensions and at subresolution scale. The last 20 years have seen the development of many different applications based on deconvolution microscopy, including a wide variety of optical setup and deconvolution algorithms. T...