• 디지털산업정보학회논문지
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• 제8권3호
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• pp.133-145
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• 2012

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.

• 디지털산업정보학회논문지
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• 제9권1호
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• pp.165-176
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• 2013

This paper introduces the high density discrete wavelet transform using quincunx sampling, which is a discrete wavelet transformation that combines the high density discrete transformation and non-separable processing method, each of which has its own characteristics and advantages. The high density discrete wavelet transformation is one that expands an N point signal to M transform coefficients with M > N. The high 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. This new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard discrete wavelet transformation in terms of shift-invariant. Although the transformation utilizes more wavelets, sampling rates are high costs and some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. A solution to this problem is a non separable method. The quincunx lattice is a non-separable 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.

• Journal of Mechanical Science and Technology
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• 제19권8호
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• pp.1611-1620
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• 2005

This paper shows the use of wavelet transformation combined with inverse acoustics to reconstruct the surface velocity of a noise source. This approach uses the boundary element analysis based on the measured sound pressure at a set of field points, the Helmholtz integral equations and wavelet transformation for reconstructing the normal surface velocity field. The reconstructed field can be diverged due to the small measurement errors in the case of nearfield acoustic holography (NAH) using an inverse boundary element method. In order to avoid this instability in the inverse problem, the reconstruction process should include some form of regularization for enhancing the resolution of source images. The usual method of regularization has been the truncation of wave vectors associated with small singular values, although the order of an optimal truncation is difficult to determine. In this paper, a wavelet transformation is applied to reduce the computation time for inverse acoustics and to enhance the reconstructed vibration field. The computational speed-up is achieved, with solution time being reduced to $14.5\%$.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.698-701
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• 2005

This paper examines that is extracted certain information in forest areas within high resolution imagery based on wavelet transformation. First of all, study areas are selected one more species distributed spots refer to forest type map. Next, study area is cut 256 x 256 pixels size because of image processing problem in large volume data. Prior to wavelet transformation, five texture parameters (contrast, dissimilarity, entropy, homogeneity, Angular Second Moment (ASM≫ calculated by using Gray Level Co-occurrence Matrix (GLCM). Five texture images are set that shifting window size is 3x3, distance .is 1 pixel, and angle is 45 degrees used. Wavelet function is selected Daubechies 4 wavelet basis functions. Result is summarized 3 points; First, Wavelet transformation images derived from contrast, dissimilarity (texture parameters) have on effect on edge elements detection and will have probability used forest road detection. Second, Wavelet fusion images derived from texture parameters and original image can apply to forest area classification because of clustering in Homogeneous forest type structure. Third, for grading evaluation in forest fire damaged area, if data fusion of established classification method, GLCM texture extraction concept and wavelet transformation technique effectively applied forest areas (also other areas), will obtain high accuracy result.

• 대한기계학회논문집A
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• 제28권1호
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• pp.70-78
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• 2004

This paper presents study of efficiency of wavelet transformation for on-line chatter detection during hard fuming process. From comparison with other time series and statistical methods such as fast fourier transformation (FFT), Kurtosis and standard deviation (STD), wavelet transform is better than others in on-line chatter detection. With using wavelet function with pseudo frequency corresponding to chatter frequency, chatter could be detected more sensitively. And for both force signal from dynamometer and displacement signal from capacitance type cylindrical sensor (CCS), wavelet transform with DB2 function on level 4 could be well used for chatter detection in hard turning process.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2011년 춘계학술대회논문집
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• pp.261-265
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• 2011

An adaptive wavelet transformation method with high order accuracy is proposed to allow efficient and accurate flow computations. While maintaining the original numerical accuracy of a conventional solver, the scheme offers efficient numerical procedure by using only adapted dataset. The main algorithm includes 3rd order wavelet decomposition and thresholding procedure. After the wavelet transformation, 3rd order of spatial and temporal accurate high order interpolation schemes are executed only at the points of the adapted dataset. For the other points, high order of interpolation method is utilized for residual evaluation. This high order interpolation scheme with high order adaptive wavelet transformation was applied to unsteady Euler flow computations. Through these processes, both computational efficiency and numerical accuracy are validated even in case of high order accurate unsteady flow computations.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권11호
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• pp.673-679
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• 2005

This Paper presents the 3D wavelet transformation based video compression system, which possesses the capability of progressive transmission by increasing resolution and increasing rate for multimedia applications. The 3D wavelet packet based video compression system removes the temporal correlation of the input sequences using the motion compensation filter and decomposes the spatio-temporal subband using the spatial wavelet packet transformation. The proposed system allocates the higher bit rate to the low frequency image of the 3D wavelet sequences and improves the 0.49dB PSNR performance of the reconstructed image in comparison with that of H.263. In addition to the limitation on the propagation of the motion compensation error by the 3D wavelet transformation, the proposed system progressively transmits the input sequence according to the resolution and rate scalability.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.39-47
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• 2023

This study compares various transformation techniques for multifocus image fusion. Multi-focus image fusion is a procedure of merging multiple images captured at unalike focus distances to produce a single composite image with improved sharpness and clarity. In this research, the purpose is to compare different popular frequency domain approaches for multi-focus image fusion, such as Discrete Wavelet Transforms (DWT), Stationary Wavelet Transforms (SWT), DCT-based Laplacian Pyramid (DCT-LP), Discrete Cosine Harmonic Wavelet Transform (DC-HWT), and Dual-Tree Complex Wavelet Transform (DT-CWT). The objective is to increase the understanding of these transformation techniques and how they can be utilized in conjunction with one another. The analysis will evaluate the 10 most crucial parameters and highlight the unique features of each method. The results will help determine which transformation technique is the best for multi-focus image fusion applications. Based on the visual and statistical analysis, it is suggested that the DCT-LP is the most appropriate technique, but the results also provide valuable insights into choosing the right approach.

• 디지털산업정보학회논문지
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• 제8권2호
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• pp.131-143
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• 2012

This paper introduces the double-density discrete wavelet transform using 3 direction separable processing method, which is a discrete wavelet transform that combines the double-density discrete wavelet transform and quincunx sampling method, each of which has its own characteristics and advantages. The double-density discrete wavelet transform is nearly shift-invariant. But 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. The dual-tree discrete wavelet transform has a more computationally efficient approach to shift invariance. Also, the dual-tree 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 double-density discrete wavelet transform using 3 direction separable processing method. The proposed wavelet transformation services good performance in image and video processing fields.

• 한국인터넷방송통신학회논문지
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• 제13권4호
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• pp.179-191
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• 2013

영상처리에서 quincunx 격자를 사용하는 기법은 대표적인 비분리의 표본화 기법이다. 이 방법은 기존의 이차원 분리가능처리 기법보다 더 많은 다양한 방향성을 가지며 대역적 특성도 우수하다. 고밀도 이산 웨이브렛 변환은 N개의 입력 신호를 M개의 변환 계수들로 확장하는 변환이다(M>N). 이차원 처리에서 이 고밀도 이산 웨이브렛 변환의 이동불변의 장점은 표준 이산 웨이브렛 변환보다 더 우수하다. 그래서 이 변환은 다른 많은 웨이브렛보다 더 유용하게 사용될 수 있지만 표본화율이 높은 단점도 존재한다. 본 논문에서는 quincunx 표본화를 사용하는 고밀도 이산 웨이브렛 변환을 제안하였다. 이 방법은 고밀도 이산 웨이브렛과 비분리 처리의 특징을 유지하고 조합하는 방법이다. 제안된 방법은 영상처리 응용분야에서 좋은 성능을 갖는다.