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Intrinsic Image Estimation and Image Deblurring for Microscopic Images (in Turkish)
Authors: Eray Dogan and Müjdat Çetin
Published in: SIU2006 - IEEE Conference on Signal Processing and Communications Applications 2006
Publication year: 2006
Abstract: Stereo microscopes used in micron-level vision research do
not directly provide the reflectivity field that we would like to
measure for a number of reasons: 1) The measurement system
causes blurring in reflectivities, 2) The measured image is a
composition of reflectivity and illumination, 3) The measured
data contain some random noise. In this work, we propose a
method for finding the reflectivity image from the measured
stereo microscopic data. First, we find the two intrinsic
images, reflectivity and illumination, that make up the
measured image. However the reflectivity component here
still contains blurring and measurement noise. We use
Tikhonov and edge-preserving regularization to deal with
these problems, and estimate the underlying reflectivity
image. We demonstrate the performance of our technique
through experimental results on real data.
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