Image compression using binary space partitioning trees.

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Image compression using binary space partitioning trees. Abstract Text:

H Radha,M Vetterli,R Leonardi,

For low bit-rate compression applications, segmentation-based coding methods provide, in general, high compression ratios when compared with traditional (e.g., transform and subband) coding approaches. In this paper, we present a new segmentation-based image coding method that divides the desired image using binary space partitioning (BSP). The BSP approach partitions the desired image recursively by arbitrarily oriented lines in a hierarchical manner. This recursive partitioning generates a binary tree, which is referred to as the BSP-tree representation of the desired image. The most critical aspect of the BSP-tree method is the criterion used to select the partitioning lines of the BSP tree representation, In previous works, we developed novel methods for selecting the BSP-tree lines, and showed that the BSP approach provides efficient segmentation of images. In this paper, we describe a hierarchical approach for coding the partitioning lines of the BSP-tree representation. We also show that the image signal within the different regions (resulting from the recursive partitioning) can be represented using low-order polynomials. Furthermore, we employ an optimum pruning algorithm to minimize the bit rate of the BSP tree representation (for a given budget constraint) while minimizing distortion. Simulation results and comparisons with other compression methods are also presented.

Image compression using binary space partitioning trees. Publishing Authors By Initials

H Radha,M Vetterli,R Leonardi,

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Image compression using binary space partitioning trees. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: IEEE transactions on image processing : a publicat

VOLUME: 5

Page Numbers: 1610-24

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ISSN: 1057-7149

DAY: 21

MONTH: 02

YEAR: 1996

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LANGUAGE: eng

NlmUniqueID: 9886191

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Grant and Affiliation Information for Image compression using binary space partitioning trees.

AFFILIATION: Philips Res. Labs., Briarcliff Manor, NY.

Country: United States

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MEDLINETA: IEEE Trans Image Process

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