Digital photograph stitching with optimized matching of gradient and curvature

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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