Retrieving Landscape Images Using Scene Structural Matrix
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Binary-Space-Partitioned Images for Resolving Image-Based Visibility
IEEE Transactions on Visualization and Computer Graphics
Genetic Evolution Processing of Classification
IEEE Transactions on Knowledge and Data Engineering
Local Experts Organization Model for Natural Scene Images Classification
Neural Processing Letters
Content adaptive mesh representation of images using binary space partitions
IEEE Transactions on Image Processing
Hierarchical segmentation-based image coding using hybrid quad-binary trees
IEEE Transactions on Image Processing
ACM Transactions on Sensor Networks (TOSN)
An energy-efficient image representation for secure mobile systems
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
A novel enhancement for hierarchical image coding
Journal of Visual Communication and Image Representation
A generalization of quad-trees applied to image coding
Integrated Computer-Aided Engineering
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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