이중 밀도 웨이브렛 변환의 성능 향상을 위한 Quincunx 표본화 기법
This paper introduces the double-density discrete wavelet transform(DWT) using quincunx sampling, which is a DWT that combines the double-density DWT and quincunx sampling method, each of which has its own characteristics and advantages. The double-density DWT is an improvement upon the critically s...
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Published in | (사)디지털산업정보학회 논문지, 8(1) Vol. 8; no. 1; pp. 171 - 181 |
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Main Authors | , , , |
Format | Journal Article |
Language | Korean |
Published |
(사)디지털산업정보학회
01.03.2012
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Subjects | |
Online Access | Get full text |
ISSN | 1738-6667 2713-9018 |
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Summary: | This paper introduces the double-density discrete wavelet transform(DWT) using quincunx sampling, which is a DWT that combines the double-density DWT and quincunx sampling method, each of which has its own characteristics and advantages. The double-density DWT is an improvement upon the critically sampled DWT with important additional properties: Firstly, It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. Secondly, the double-density DWT is overcomplete by a factor of two, and Finally, it is nearly shift-invariant. In two dimensions, this transform outperforms the standard DWT in terms of denoising; however, there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. A solution to this problem is a quincunx sampling method. The quincunx lattice is a sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Proposed wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, This method services good performance in image processing fields. |
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Bibliography: | G704-SER000010259.2012.8.1.019 |
ISSN: | 1738-6667 2713-9018 |