본문 바로가기
KERD
논문KCI 등재

3중 밀도 이산 웨이브렛 변환을 이용한 디지털 영상처리 기법

The Digital Image Processing Method Using Triple-Density Discrete Wavelet Transformation

2

조회

0

다운로드

4

인용

0

참고문헌

키워드

초록

This paper describes the high density discrete wavelet transformation which is one that expands an N point signal to M transform coefficients with M > N. The double-density discrete wavelet transform is one of the high density discrete wavelet transformation. This transformation employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is nearly shift-invariant. Similarly, triple-density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. Specifically, the spectrum of the first wavelet is concentrated halfway between the spectrum of the second wavelet and the spectrum of its dilated version. In addition, the second wavelet is translated by half-integers rather than whole-integers in the frame construction. This arrangement leads to high density wavelet transformation. But this new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard and double-density discrete wavelet transformation in terms of multiple directions. Resultingly, the proposed wavelet transformation services good performance in image and video processing fields.

Abstract

This paper describes the high density discrete wavelet transformation which is one that expands an N point signal to M transform coefficients with M > N. The double-density discrete wavelet transform is one of the high density discrete wavelet transformation. This transformation employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is nearly shift-invariant. Similarly, triple-density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. Specifically, the spectrum of the first wavelet is concentrated halfway between the spectrum of the second wavelet and the spectrum of its dilated version. In addition, the second wavelet is translated by half-integers rather than whole-integers in the frame construction. This arrangement leads to high density wavelet transformation. But this new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard and double-density discrete wavelet transformation in terms of multiple directions. Resultingly, the proposed wavelet transformation services good performance in image and video processing fields.

참고문헌 (6)

  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, "A higher-density discrete wavelet transform", IEEE Trans. on Signal Processing, 54(8), pp.3039~3048 (2006)
  5. 임중희, "이중 밀도 웨이브렛 변환의 성능 향상을 위한 Quincunx 표본화 기법", (사)디지털산업정보학회 논문지, 8(1), pp.171~181 (2012), (사)디지털산업정보학회
  6. 신종홍, "이중 밀도 웨이브렛 변환의 성능 향상을 위한 3방향 분리 처리 기법", (사)디지털산업정보학회 논문지, 8(2), pp.131~143 (2012), (사)디지털산업정보학회[DOI]

관련 논문AI추천

이 간행물의 다른 논문 (18건)