Scarmana, G. (2011) Image reconstruction in the contour domain. In: ISDE 7: 7th International Symposium on Digital Earth , 23-25 Aug 2011, Perth, Australia.
PDF (Accepted Version)
Digital image enhancement systems are essentially pixel-based. In this paper, a novel method of multi-frame image enhancement employs contours rather than pixels as the primitive working unit. The feasibility of this proposal is based on the fact that gray-scale images can be sufficiently and accurately represented by their contour maps if a suitable contour model and scale selection method
is used .
In this process several low-resolution shifted frames of the same scene are (a) registered (b) transformed into their contour domain, and (c) grouped or mapped globally within a singular framework to create an enhanced contour composite. Inverting this improved contour representation
yields a high-fidelity reconstruction of an image in pixel format with more details than any of the original input frames.
The mapping of the low-resolution contour images within a singular framework takes advantage of the differences (or shifts) existing between their contour representations. These shifts are computed using an innovative image registration technique that can achieve accuracies of up to 0.01 of a pixel. The technique is based on DCT (Discrete Fourier Transforms) and normalized cross-correlation.
Controlled tests show that this global contour mapping approach, with subsequent converting to a compact and improved raster image, provides for an efficient and simplified method for multi-frame image enhancement. As compared to pixel-based multi-frame image enhancement processes, the proposed method may be computationally more efficient as it allows the detection, filtering and
elimination of redundant contour data which may have little or no effect in the final enhancement.
Although still in the experimental stage and restricted to gray-scale images, the proposed method is particularly viable in applications involving facial enhancements of compressed video frames.
Statistics for this ePrint Item
|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Item Status:||Live Archive|
|Additional Information:||No evidence of copyright restrictions preventing deposit.|
|Depositing User:||Dr Gabriel Scarmana|
|Faculty / Department / School:||Historic - Faculty of Engineering and Surveying - Department of Surveying and Land Information|
|Date Deposited:||23 Sep 2011 01:22|
|Last Modified:||22 Sep 2014 23:00|
|Uncontrolled Keywords:||image processing; contours; image editing|
|Fields of Research :||09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010303 Optimisation
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
|Socio-Economic Objective:||E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering|
Actions (login required)
|Archive Repository Staff Only|