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디지털 영상 처리를 위한 Quincunx 표본화가 사용된 이중 트리 이산 웨이브렛 변환

Dual-tree Wavelet Discrete Transformation Using Quincunx Sampling For Image Processing

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초록

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. DDWT main property is a more computationally efficient approach to shift invariance. Also, the DDWT gives much better directional selectivity when filtering multidimensional signals. The dual-tree DWT of a signal is implemented using two critically-sampled DWTs in parallel on the same data. The transform is 2-times expansive because for an N-point signal it gives 2N DWT coefficients. If the filters are designed is a specific way, then the sub-band signals of the upper DWT can be interpreted as the real part of a complex wavelet transform, and sub-band signals of the lower DWT can be interpreted as the imaginary part. The quincunx lattice is a sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Quincunx lattice yields a non separable 2D-wavelet transform, which is also symmetric in both horizontal and vertical direction. And non-separable wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, non-separable image processing using DDWT services good performance.

Abstract

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. DDWT main property is a more computationally efficient approach to shift invariance. Also, the DDWT gives much better directional selectivity when filtering multidimensional signals. The dual-tree DWT of a signal is implemented using two critically-sampled DWTs in parallel on the same data. The transform is 2-times expansive because for an N-point signal it gives 2N DWT coefficients. If the filters are designed is a specific way, then the sub-band signals of the upper DWT can be interpreted as the real part of a complex wavelet transform, and sub-band signals of the lower DWT can be interpreted as the imaginary part. The quincunx lattice is a sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Quincunx lattice yields a non separable 2D-wavelet transform, which is also symmetric in both horizontal and vertical direction. And non-separable wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, non-separable image processing using DDWT services good performance.

참고문헌 (7)

  1. N. G. Kingsbury, "Complex wavelets for shift invariant analysis and filtering of signals", Appl. Comput. Harmon. Anal, 10(3), pp.234~253 (2001)
  2. Jingyu Yang, "Image Coding Using Dual-Tree Discrete Wavelet Transform", IEEE Trans. on Image Processing, 17(9), pp.1555~1569 (2008)
  3. J. Kovacevic, "Wavelet families of increasing order in arbitrary dimensions", IEEE Trans. on Image Processing, 9(3), pp.480~496 (2000)
  4. Joonghee Lim, "Non-separable Image Processing Using Dual-Tree Complex Wavelet Transformation", ITC-CSCC 2011, ~ (2011)
  5. 신종홍, "자유시점 TV를 위한 다시점 비디오의 계층적 깊이 영상 표현과 H.264 부호화", (사)디지털산업정보학회 논문지, 7(2), pp.91~100 (2011), (사)디지털산업정보학회
  6. 조범석, "비디오 준무손실 압축을 위한 효율적인 레이트 컨트롤 알고리즘", (사)디지털산업정보학회 논문지, 6(2), pp.11~17 (2010), (사)디지털산업정보학회
  7. 정수목, "영상의 지역성을 이용한 보간 영상의 화질 개선 기법", (사)디지털산업정보학회 논문지, 6(4), pp.217~223 (2010), (사)디지털산업정보학회

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