이중 밀도 웨이브렛 변환의 성능 향상을 위한 Quincunx 표본화 기법
Quincunx Sampling Method For Improvement of Double-Density Wavelet Transformation
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초록
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.
Abstract
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.
참고문헌 (8)
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- Jingyu Yang, "Image Coding Using Dual-Tree Discrete Wavelet Transform", IEEE Trans. on Image Processing, 17(9), pp.1555~1569 (2008)
- I. W. Selesnick, "The double-density dual-tree DWT", IEEE Trans. on Signal Processing, 52(5), pp.1304~1314 (2004)
- W. Selesnick, "The double density DWT, In Wavelets in signal and Image Analysis: From Theory to Practice" (2001), Kluwer
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- 신종홍, "디지털 영상 처리를 위한 Quincunx 표본화가 사용된 이중 트리 이산 웨이브렛 변환", (사)디지털산업정보학회 논문지, 7(4), pp.119~131 (2011), (사)디지털산업정보학회
- Joonghee Lim, "Non-separable Image Processing Using Dual-Tree Complex Wavelet Transformation,", ITC-CSCC 2011, ~ (2011)
- 신종홍, "자유시점 TV를 위한 다시점 비디오의 계층적 깊이 영상 표현과 H.264 부호화", (사)디지털산업정보학회 논문지, 7(2), pp.91~100 (2011), (사)디지털산업정보학회
