• Title/Summary/Keyword: Dual Tree Discrete Wavelet Transform(DDWT)

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Dual-tree Wavelet Discrete Transformation Using Quincunx Sampling For Image Processing (디지털 영상 처리를 위한 Quincunx 표본화가 사용된 이중 트리 이산 웨이브렛 변환)

  • Shin, Jong Hong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.7 no.4
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    • pp.119-131
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    • 2011
  • 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.

A Study on Enhancement of Digital Image Performance Using Dual Tree Wavelet Transformation in Non-separable Image Processing (비분리 영상처리에서 이중 트리 웨이브렛 변환을 사용한 디지털 영상 성능 개선에 관한 연구)

  • Lim, Joong-Hee;Jee, Inn-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.1
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    • pp.65-74
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    • 2012
  • 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 introduces limited redundancy and allows the transform to provide approximate shift invariance and directionally selective filters while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. Also, 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. The proposed 2-D non-separable DDWT can provide efficient approximation for directional features of images schemes, such as edges and contours in images that are not aligned with the horizontal or vertical direction. Finally, non-separable image processing using DDWT services good performance.