Digital photograph stitching blends multiple images to form a single
one with a wide field of view. Sometimes, artifacts may arise, often
due to photometric inconsistency and geometric misalignment among
the images. Several existing techniques tackle this problem by
methods such as pixel selection or pixel blending, which involve the
matching of intensity, frequency, and gradient among the input
images and adjust them to find the optimal match with the input
images. However, our experience indicates that these methods have
yet fully incorporated the mathematical properties of the
photometric inconsistency. In this paper, we first introduce a
general mathematical model describing the properties and effects of
the photometric inconsistency. This model supports our claim that
matching on the intensity and even the gradient domain is
insufficient. Our method thus adds the extra requirement of an
optimal matching of curvature. Simulations are carried out using our
method, with input images suffering from different kinds of
photometric inconsistency under the aligned and misaligned
situations. We evaluate the results using both objective and
subjective criteria, and we find that our method indeed shows an
improvement for certain kinds of photometric inconsistency.
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