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Seamless photography: Using mathematical models for image stitching

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Posted October 3, 2013
A photo captures only as much as the camera in use will allow, and is therefore limited by the field of view of the camera’s lens. In the case of smartphones and many advanced cameras, the view from the lens is much smaller than the view from your own eyes.
Seamless photography: Using mathematical models for image stitching
This shows two input images (from left) stitched together using the proposed method (right). Credit: original image: Blanka M. Lukes, Prague Private Guides; modified image: Wei Wang and Michael Ng.

Panoramic photographs were invented to capture large objects or scenes that could not otherwise fit within the constraints of a single photo. Panoramic photography is achieved through image stitching, a process that combines two or more photographs, seamlessly blending input images with overlapping regions into one picture. A paper published by Wei Wang and Michael Ng in the SIAM Journal on Imaging Sciencesthis summer aims to develop an algorithm for image stitching.

Image stitching involves two steps: image alignment and image blending. Image alignment finds point pairs in the overlapping region of two images that correspond to one another. Image blending combines the two aligned images seamlessly. This step is important if the pixel intensities in the different images vary enough to produce artifacts such as varying lighting conditions and different exposure settings. In this paper, the authors focus on image blending, assuming that the images have been aligned.

Many different approaches for image blending are seen in the literature. “The traditional method is to search for a curve in the overlapping area in which the differences among the input images are minimal,” explains author Michael Ng. “However, the curve may not be determined accurately because of light intensity, color inconsistency, parallax, occlusion, etc.”

Read more at: Phys.org

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