ACM SIGGRAPH 2006 Papers
Schematic storyboarding for video visualization and editing
ACM SIGGRAPH 2006 Papers
An Image Completion Algorithm Using Occlusion-Free Images from Internet Photo Sharing Sites
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
A color adjustment method for automatic seamless image blending
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: interaction platforms and techniques
Eliminating structure misalignments using robust matching and image editing based on seam carving
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Edge-constrained image compositing
Proceedings of Graphics Interface 2011
Towards obtaining an ideal real time panoramic video
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
Parallel patch-based texture synthesis
EGGH-HPG'12 Proceedings of the Fourth ACM SIGGRAPH / Eurographics conference on High-Performance Graphics
Image composition with blurring effect from depth of field
ICEC'07 Proceedings of the 6th international conference on Entertainment Computing
Variable homography compensation of parallax along mosaic seams
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Stitching line and deformation propagation for seamless image stitching
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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The aim of this paper is to achieve seamless image stitching for eliminating obvious visual artifact caused by severe intensity discrepancy, image distortion and structure mis-alignment, given that the input images are globally registered. Our approach is based on structure deformation and propagation while maintaining the overall appearance affinity of the result to the input images. This new approach is proven to be effective in solving the above problems, and has found applications in mosaic deghosting, image blending and intensity correction. Our new method consists of the following main processes. First, salient features or structures are robustly detected and aligned along the optimal partitioning boundary between the input images. From these features, we derive sparse deformation vectors to uniformly encode the underlying structure and intensity misalignment. These sparse deformation cues will then be propagated robustly and smoothly into the interior of the target image by solving the associated Laplace equations in the image gradient domain. We present convincing results to show that our method can handle significant structure and intensity misalignment in image stitching.