Scarmana, Gabriel (2011) Compressing images using contours. In: 2011 Surveying and Spatial Sciences Conference: Innovation in Action: Working Smarter (SSSC 2011), 21-25 Nov 2011, Wellington, New Zealand.
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A method for the vectorisation of digital images into contour maps with subsequent conversion of the contours to a pixel format is presented. This method may offer an alternative spatial image compression which is computationally inexpensive and can be directly applied to compressing certain classes of grey-scale and/or colour (RGB, 24 bits) imagery of any size.
The feasibility of this study is based on research which shows that pixel based imagery can be sufficiently and accurately represented by their contour maps if a suitable contour model and scale selection method is used (Elder and Goldberg, 2001).
The compression process is based on filtering and eliminating those contours that may contain redundant information. Contours extracted from digital images may contain multiple redundant data (i.e. intersecting or nested contours), any of which might logically be used as a basis for discrimination or, on the other hand, used in the reconstruction of an original captured
As per current image compression techniques the proposed method does not require special hardware and, if combined with existing encoding schemes, it can be efficiently used for image transmission purposes due to its relatively modest storage requirements. Depending on the applications, and the amount of contour lines employed in the reconstruction of an image, the process allows for various levels of image accuracy while preserving visual integrity and reducing compression artifacts
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|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Item Status:||Live Archive|
|Additional Information:||This work is licensed under a Creative Commons Attribution 3.0 New Zealand License.|
|Depositing User:||Dr Gabriel Scarmana|
|Faculty / Department / School:||Historic - Faculty of Engineering and Surveying - Department of Surveying and Land Information|
|Date Deposited:||23 May 2012 04:55|
|Last Modified:||12 Aug 2014 04:24|
|Uncontrolled Keywords:||contouring; image compression; image reconstruction; image processing; 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 > 970110 Expanding Knowledge in Technology|
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