Image stitching and object insertion in the gradient domain
| dc.contributor.author | Sevcenco, Ioana Speranta | |
| dc.contributor.supervisor | Agathoklis, Panajotis | |
| dc.date.accessioned | 2011-12-20T19:56:36Z | |
| dc.date.available | 2011-12-20T19:56:36Z | |
| dc.date.copyright | 2011 | en_US |
| dc.date.issued | 2011-12-20 | |
| dc.degree.department | Department of Electrical and Computer Engineering | |
| dc.degree.level | Master of Applied Science M.A.Sc. | en_US |
| dc.description.abstract | In this thesis, the applications of image stitching and object insertion are considered and two gradient based approaches offering solutions are proposed. An essential part of the proposed methods is obtaining an image from a given gradient data set. This is done using an existing Haar wavelet based reconstruction technique, which consists of two main steps. First, the Haar wavelet decomposition of the image to be reconstructed is obtained directly from a given gradient. Second, the image is obtained using Haar wavelet synthesis. In both stitching and object insertion applications considered, the gradient from which the image must be reconstructed is a non-conservative vector field and this requires adding an iterative Poisson solver at each resolution level, during the synthesis step of the reconstruction technique. The performance of the reconstruction algorithm is evaluated by comparing it with other existing techniques, in terms of solution accuracy and computation speed. The proposed image stitching technique consists of three main parts: registering the images to be combined, blending their gradients over a region of interest and obtaining a composite image from a gradient. The object insertion technique considers the images registered and has two main stages: gradient blending of images in a region of interest and recovering an image from the gradient. The performance of the stitching algorithm is evaluated visually, by presenting the results produced to combine images with varying orientation, scales, illumination, and color conditions. Experimental results illustrate both the stitching and the insertion techniques proposed, and indicate that they yield seamless composite images. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.bibliographicCitation | I.S. Sevcenco, P.J. Hampton, and P. Agathoklis. Seamless stitching of images based on a Haar wavelet 2D integration method. In 17th International Conference on Digital Signal Processing (DSP), pages 1–6, Jul. 2011. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/3753 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights.temp | Available to the World Wide Web | en_US |
| dc.subject | image stitching | en_US |
| dc.subject | object insertion | en_US |
| dc.subject | image reconstruction from gradient measurements | en_US |
| dc.subject | Poisson equation | en_US |
| dc.title | Image stitching and object insertion in the gradient domain | en_US |
| dc.type | Thesis | en_US |