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Hybrid image representation using quadtree and OBDD

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dc.contributor.author Handoko en_US
dc.date.accessioned 2015-01-12T10:39:40Z
dc.date.available 2015-01-12T10:39:40Z
dc.identifier.other AIT Thesis no.CS-02-10 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/226
dc.description Bangkok : Asian Institute of Technology, 2002 en_US
dc.description 50 p. en_US
dc.description.abstract Ordered Binary Decision Diagra m (OBDD) has been used to reduce the amount of space and computational required for verify ing digital circuits by removing copies of sub-functions in Boolean function. An image can be processed as Boolean func tion as it is assigned with variables along x and y coordinates. The number of variables in OBDD will effect to the performance of OBDD in terms of ratio and ti me. Quadtree is a spatial image compression algorithm that has been widely used to represent images such in GIS or medical X-Ray. It is a fast algorithm that divides an area into quadran ts and recursively divides each quadrant into smaller ones until the area cannot be divided into smaller parts anymore. By combining these two algorithms, an image can be processed using various sizes of OBDD depends on the characteristics of block th at will be processed. Lossless image compression using Quadtree-OB DD typically produces average compression ratios 1.25 for natural images, 3.29 for text images, 7.49 for binary images, 30.19 for synthetic images and 1.02 for texture images. These result s are better than GIF algorithm for all image classifications except text images and bette r than Lossless JPEG for binary images.
dc.relation.ispartof Thesis no. CS-02-10 en_US
dc.relation.ispartof Asian Institute of Technology. Thesis no. CS-02-10 en_US
dc.subject Image compression en_US
dc.title Hybrid image representation using quadtree and OBDD en_US
dc.type Thesis en_US


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