• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.37 no.7
• /
• pp.498-509
• /
• 1988

A BF(breadth-first) linear quadtree as a new data structure for image data is suggested, which enables us to compress the image data efficiently and to make operations of the compressed data easily. It is a list of path names for black nodes as the linear quadtree is. The path name for each black node of a BF linear quadtree is represented as a sequence of path codes from the root node to itself, whereas that of linear quadtree as a sequence of path codes from the root node to itself and fill characters for cut-offed path from it to any n-level node which corresponds to a pixel of an image. The BF linear quadtree provides a more efficent compression ratio than the linear quadtree does, because the former does not require redundant characters, fill characters, for the cut-offed paths. Several operations for image processing can be also implemented on this hierarchical structure efficiently, because it is composed of only the black nodes ad the linear quadtree is . In this paper, algorithms for several operations on the BF linear quadtree are defined and analyzed. Experimental results for forur image data are also given and discussed.

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

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.362-364
• /
• 1999

본 논문에서는 Quadtree 구조를 기반으로 한 효율적인 색상 정보 추출과 영상 검색을 수행하는 시스템을 구현한다. 제시한 시스템은 원 영상으로부터 DC영상을 추출하고, DC 영상의 화소들을 RGB에서 HSV의 색상 좌표계로 변환한다. 변환된 영상에서 색상의 분포에 따라 Quadtree 형태로 영역을 분할하고 대표 색상을 추출한다. 마지막으로 추출한 색상과 그 색상의 분포에 따라 Quadtree 형태로 영역을 분할하고 대표 색상을 추출한다. 마지막으로 추출한 색상과 그 색상의 분포값을 영역의 위치에 따라 Quadtree의 단말 노드에 저장한다. 그리고, 사용자가 질의 영상을 주었을 때 Quadtree에 저장된 정보를 이용하여 본 논문에서 제안한 유사도 측정을 통하여 결과 영상을 보여준다. 본 논문에서 제안한 방법으로 실험한 결과 64개의 영역으로 나눈 방법에 비해 비교하는 평균 영역의 개수는 28.9개였고, 검색시간은 2~6초 정도 감소하였다. 또한, 전체 영상의 색상 정보 저장량도 25% 정도 줄어들었지만 질의에 대한 두 방법의 검색 결과는 유사하게 나타났다.

• Journal of the Korea Computer Graphics Society
• /
• v.15 no.3
• /
• pp.27-33
• /
• 2009

In terrain visualization, the quadtree is the most frequently used data structure for progressive mesh generation. The quadtree provides an efficient level-of-detail selection and view frustum culling. However, most applications using quadtrees are performed by the CPU, since the hierarchical data structure cannot be manipulated in a programmable rendering pipeline. For this reason, quadtree-based methods show lower performance and higher dependancy of CPU in comparison to GPU-based methods. We present a quadtree-based terrain-rendering method for GPU execution that uses vertex multiplication. It offers higher performance than previous CPU-based quadtree methods, without loss of image quality.

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

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.7
• /
• pp.1613-1623
• /
• 1996

In this paper, an image coding scheme using removal of isolated coefficients and quadtree structure in wavelet transformed domain, is suggested. The number of significant coefficients can be reduced by quantizing in different stages according to the weights of the each band. The quadtree structure preseves the location information while significantly reducing the number of bits required to represent the locality of an image. To increase the efficienty of the wavelet transformed images using quadtree, the energy of the isolated coefficients is analyzed and those with low energy are eliminated. Furthermore, to control the bit rate the entropy of each block is sorted according to its energy concentration and the number of bits required for encoding, and the blocks with low energy are removed to achieve the desired compression rate.

• ETRI Journal
• /
• v.11 no.1
• /
• pp.109-122
• /
• 1989

We developed new quadtree and octree representation schemes which reduce the storage requirements from exponential to polynomial. The new schemes not only lessen the large storage requirements of the existing quadtree and octree representation schemes but guarantee an exact representation of the original object. These are made possible by adopting a new set of termination conditions that ensure finiteness of the quadtree and octree during the decomposition. These new data structures are analyzed theoretically and tested empirically. For space complexity, we analyzed its best case, worst case, and average case. Given an $n_e$-gon, we show that the expected number of nodes in our quadtree isO($$$n_e^1.292$) For a polyhedron with $n_f$ faces, the expected number of nodes in the new octree is O($$$n_f^1.667$). For time complexity, we again analyzed the best, worst, and average cases for constructing such quadtree and octree and find the average to be the same as those of the space complexity. Finally, random $n_e$- gons are generated as test data. Regression equations are fitted and are shown to support the claims on the average case performance.

• Proceedings of the KIEE Conference
• /
• 1991.11a
• /
• pp.201-204
• /
• 1991

In this paper the method of representing the document image by the quadtree data structure, and extracting each character seperately from the constructed quadtree are described. The document image is represented by a binary encoded quadtree and the segmentation is performed according to the information of each leaf node of the quadtree. Then, each character is extracted by the relation of positions of segments. This method enables to extract characters without examining every pixel in the image and the required storage of document image is decreased.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.5
• /
• pp.1825-1839
• /
• 2015

The final draft of the latest video coding standard, High Efficiency Video Coding (HEVC), was approved in January 2013. The coding efficiency of HEVC surpasses its predecessor, H.264/MPEG-4 Advanced Video Coding (AVC), by using only half of the bitrate to encode the same sequence with similar quality. However, the complexity of HEVC is sharply increased compared to H.264/AVC. In this paper, a method is proposed to decrease the complexity of intra coding in HEVC. Early pruning and an early splitting strategy are applied to the quadtree structure of coding tree units (CTU) and residual quadtree (RQT). According to our experiment, when our method is applied to sequences from Class A to Class E, the coding time is decreased by 44% at the cost of a 1.08% Bjontegaard delta rate (BD-rate) increase on average.

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