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이중 밀도 웨이브렛 변환의 성능 향상을 위한 3방향 분리 처리 기법

The Three Directional Separable Processing Method for Double­Density Wavelet Transformation Improvement

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초록

This paper introduces the double­density discrete wavelet transform using 3 direction separable processing method, which is a discrete wavelet transform that combines the double­density discrete wavelet transform and quincunx sampling method, each of which has its own characteristics and advantages. The double­density discrete wavelet transform is nearly shift­invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double­density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. The dual­tree discrete wavelet transform has a more computationally efficient approach to shift invariance. Also, the dual­tree discrete wavelet transform gives much better directional selectivity when filtering multidimensional signals. But this transformation has more cost complexity Because it needs eight digital filters. Therefor, we need to hybrid transform which has the more directional selection and the lower cost complexity. A solution to this problem is a the double­density discrete wavelet transform using 3 direction separable processing method. The proposed wavelet transformation services good performance in image and video processing fields.

Abstract

This paper introduces the double­density discrete wavelet transform using 3 direction separable processing method, which is a discrete wavelet transform that combines the double­density discrete wavelet transform and quincunx sampling method, each of which has its own characteristics and advantages. The double­density discrete wavelet transform is nearly shift­invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double­density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. The dual­tree discrete wavelet transform has a more computationally efficient approach to shift invariance. Also, the dual­tree discrete wavelet transform gives much better directional selectivity when filtering multidimensional signals. But this transformation has more cost complexity Because it needs eight digital filters. Therefor, we need to hybrid transform which has the more directional selection and the lower cost complexity. A solution to this problem is a the double­density discrete wavelet transform using 3 direction separable processing method. The proposed wavelet transformation services good performance in image and video processing fields.

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 DualTree Discrete Wavelet Transform", IEEE Trans. on Image Processing, 17(9), pp.1555~1569 (2008)
  3. I. W. Selesnick, "The doubledensity dualtree DWT", IEEE Trans. on Signal Processing, 52(5), pp.1304~1314 (2004)
  4. I. W. Selesnick, "The double density Dual –Tree DWT", IEEE Trans. on Signal Processing, 52(5), pp.304~1314 (2004)
  5. Kovacevic, "Wavelet families of increasing order in arbitrary dimensions", IEEE Trans. on Image Processing, 9(3), pp.480~496 (2000)
  6. 신종홍, "디지털 영상 처리를 위한 Quincunx 표본화가 사용된 이중 트리 이산 웨이브렛 변환", (사)디지털산업정보학회 논문지, 7(4), pp.119~131 (2011), (사)디지털산업정보학회
  7. 임중희, "이중 밀도 웨이브렛 변환의 성능 향상을 위한 Quincunx 표본화 기법", (사)디지털산업정보학회 논문지, 8(1), pp.171~181 (2012), (사)디지털산업정보학회

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