• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2247-2258
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• 1997

Quadtree, which is hierarchical data structure, is a very important data structure to represent binary images. Since a linear quadtree representation as is a way to store a quadtree is efficient to save space compared with other representations. It is, however, complicated and takes a large amount of time to build the linear quadtree. In this paper, we present O(1) time a linear quadtree building algorithm for a $n{\times}n$ binary image using three-dimensional $n{\times}n{\times}n$ processors on RMESH structure. Our algorithm, by use of O(1) time collapsing algorithm and reported O(1) time sorting algorithm, is simpler and easier to understand than resently presented algorithm on PARBUS structure.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.4
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• pp.369-378
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• 2000

Conventional fractal image compression methods have many problems in searching time for matching domain block. Proposed method is an improved method of Fisher's Quadtree Decomposition in terms of time, compression ratio, and PSNR. This method determines range block in advance using QR algorithm. First, input image is partitioned to $4{\times}4$ range block and then recomposition is performed from bottom level to specified level. As a result, this proposed method achieves high encoding and decoding speed, high compression ratio, and high PSNR than Fisher's Quadtree Decomposition method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.873-876
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• 2003

Z-map model is the most widely used model for NC simulation and verification. But it has several limitations to get a high precision, to apply 5 axis machining simulation. In this paper, we tried to use quadtree for searching cutting region. Quadtree representation of two dimensional objects is performed with a tree that describes the recursive subdivision. By using these quadtree model. storage requirements were reduced. And also, recursive subdivision was processed in the boundries, so, useless computation could be reduced, too. To get more high Accuracy, we applied the supersampling method in the boundaries. The Supersampling method is the most common form of the antialiasing and usually used with polygon mesh rendering in computer graphics To verify quadtree model we compared simulated results with z-map model and enhanced z-map model

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.1-10
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• 1992

This study presents a complete octree construction algorithm for 2D depth images obtained from orthogonal face views, which can represent 3D objects exactly. In constructing quadtree, optimal quadtree construction algorithm is applied to depth images for efficient use of memory and reduction of tree construction time. In addition, pseudo-octrees are constructed by using our proposed method, which construct pseudo-octrees according to the resolution value given in each node of constructed quadtree and mapping relation between quadrants and octants. Finally, a complete octree, which represents a 3D object, is constructed by volume intersection with each constructed pseudo-octree. The representation accuracy of a complete octree constructed by our algorithm is investigated by using a 3D display method and a volume ratio method for a complete octree.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.489-495
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• 2010

Hyperspectral imaging obtains information with a wider wavelength range a large number of bands. However, a high correlation between each band, computation cost, and noise causes inaccurate results in cases of no pre-processing. The noises of band extraction and elimination positively necessary in hyperspectral imaging. Since the previous studies have used a characteristic the whole image, a local characteristic of the image is considered for the noise band extraction. In this study, the Quadtree, which is a data structure algorithm. and the fractal dimension are adopted for noise band extraction in Hyperion images. The fractal dimensions of the segments divided by the Quadtree structure are calculated, and variation is used. We focused on the extraction of random noise bands in Hyperion images and compared them with the reference data made by visual decisions. The proposed algorithm extracts the most bands, including random noises. It is possible to eliminate more than 30 noise bands, regardless of images.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.55-59
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• 1990

This study presents new algorithm for generating octree by volume intersection with pseudo-octrees which are constructed for each orthogonal face views in order to represent 3D objects exactly. In this algorithm, optimal quadtree is constructed for depth images in which distance information is represented in gray level, and then pseudo-octrees are constructed by using optimal quadtree in each orthogonal face view. It is shown that 3D object with concave parts can be reconstructed exactly by our suggested algorithm, and that memory space and tree construction time are also reduced compared with other algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.10-18
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• 2004

Quadtree, which is a hierarchical data structure, is a very important data structure to represent binary images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The operations of unaligned linear quadtrees, which are operations among the linear quadtrees with different origin, are able to perform the translated or rotated images efficiently. And this operations requires alignment of the linear quadtrees. In this paper, we present an efficient algorithm to perform alignment of unaligned linear quadtrees, using three-dimensional $n{\pm}n{\pm}n$ processors on RMESH(Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to route the locational codes of quardtree on the hierarchical structure of $n{\pm}n{\pm}n$ RMESH.

• The KIPS Transactions:PartA
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• v.14A no.3 s.107
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• pp.151-158
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• 2007

Quadtree, which is a hierarchical data structure, is a very important data structure to represent images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The computation of block location is one of important geometry operations in image processing, which extracts a component completely including a given block. In this paper, we present a constant time algorithm to compute the block location of images represented by quadtrees, using three-dimensional $n\times n\times n$ processors on RMESH(Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to deal with the locational codes of quardtree on the hierarchical structure of $n\times n\times n$ RMESH.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.41-47
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• 2011

Processing of the raw LiDAR data requires the high-end processor, because data form is a vector. In contrast, if LiDAR data is converted into a regular grid pattern by filltering, that has advantage of being in a low-cost equipment, because of the simple structure and faster processing speed. Especially, by using grid data classification, such as Quadtree, some of trees and cars are removed, so it has advantage of modeling. Therefore, this study presents the algorithm for automatic extraction of ground points using Quadtree and refion growing method from LiDAR data. In addition, Error analysis was performed based on the 1:5000 digital map of sample area to analyze the classification of ground points. In a result, the ground classification accuracy is over 98%. So it has the advantage of extracting the ground points. In addition, non-ground points, such as cars and tree, are effectively removed as using Quadtree and region growing method.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.95-103
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• 2001

Rendering of 3D terrain data in real-time is difficult because of its large scale. So, it is necessary to use level-of-detail(LOD) that uses fewer data, but makes almost similar image to the original. We present an algorithm for real-time LOD generation and rendering of 3D terrain data. The algorithm applies wavelet transform to the terrain data, and then generates quadtree based view-dependent LOD using wavelet coefficients that are the output of wavelet transform. It also uses frame-to-frame coherence and view culling for high frame rates.