Curvature Domain Image Stitching

Digital photograph stitching blends multiple images to form a single one with a wide field of view. However, 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 and adjustment of intensity, frequency, and gradient values. However, our experience indicates that these methods have yet fully incorporated the uniformity properties of the photometric inconsistency. In this paper, we first explain the causes of inconsistency and its uniformity property. Then, by mathematical analysis, we show that the matching on the intensity and even the gradient domain is insufficient for some non-uniform inconsistencies. Our method thus adds the extra requirement of an optimal matching of curvature. We then explain how its variables can affect the computational and visual performance. Simulations are carried out using our method, with some masks designed with these two concerns. Some real examples show that our method can produce pleasant visual results even when both misalignment and non-uniform inconsistency exist.