• ETRI Journal
• /
• v.25 no.5
• /
• pp.345-355
• /
• 2003

In this paper, we propose a method for designing a class of M-channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop-band attenuation, which is also taken care of in the proposed algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.3
• /
• pp.87-92
• /
• 2008

In this paper, certain scaling functions are generated using the dyadic subband tree structure and applied to a time-hopping, pulse position modulation, ultra-wideband (TH-PPM UWB) system. Scaling functions can be obtained by iterating a lowpass filter at each level using a critically sampled dyadic tree. The performance of the TH-PPM UWB system employing scaling functions as the mono-cycle waveform is evaluated through computer simulations in a Rayleigh fading environment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.3C
• /
• pp.119-124
• /
• 2005

In this paper, we propose a novel algorithm for determining the variable size of locally adaptive window using region-merging method. A region including a denoising point is partitioned to disjoint sub-regions. Locally adaptive window for denoising is obtained by selecting Proper sub-lesions. In our method, nearly arbitrarily shaped window is achieved. Experimental results show that our method outperforms other critically sampled wavelet denoising scheme.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.1
• /
• pp.171-181
• /
• 2012

This paper introduces the double-density discrete wavelet transform(DWT) using quincunx sampling, which is a DWT that combines the double-density DWT and quincunx sampling method, each of which has its own characteristics and advantages. The double-density DWT is an improvement upon the critically sampled DWT with important additional properties: Firstly, It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. Secondly, the double-density DWT is overcomplete by a factor of two, and Finally, it is nearly shift-invariant. In two dimensions, this transform outperforms the standard DWT in terms of denoising; however, 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. A solution to this problem is a quincunx sampling method. The quincunx lattice is a 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 Korea Society of Digital Industry and Information Management
• /
• v.7 no.4
• /
• pp.119-131
• /
• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.221-232
• /
• 2012

The double-density discrete wavelet transform(DWT) is an improvement upon the critically sampled DWT with important additional properties. It employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is overcomplete by a factor of two. Also, this transformation 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. Proposed method is a DWT that combines the double-density DWT and quincunx sampling, each of which has its own characteristics and advantages. Especially, the quincunx sampling treats the different directions more homogeneously. As a result, since proposed method can generate sub-images of multiple degrees rotated versions, this method provides an improved performance in image processing fields.

• Journal of Korean Society of Environmental Engineers
• /
• v.29 no.8
• /
• pp.895-903
• /
• 2007

As for the increasing demanding on the development of direct-ecological landfill monitoring methods, it is needed for critically defining the condition of landfills and their influence on the environment, quantifying the amount of enzymes and bacteria mainly concerned with biochemical reaction in the landfills. This study was thus conducted to understand the fates of contaminants in association with groundwater quality parameters. For the study, groundwater was seasonally sampled from four closed unsanitary landfills(i.e. Cheonan(C), Wonju(W), Nonsan(N), Pyeongtaek(P) sites) in which microbial diversity was simultaneously obtained by 16S rDNA methods. Subsequently, a number of primer sets were prepared for quantifying the specific gene of representative bacteria and the gene of encoding enzymes dominantly found in the landfills. The relationship between water quality parameters and gene quantification were compared based on correlation factors. Correlation between DSR(Sulfate reduction bacteria) gene and BOD(Biochemical Oxygen Demand) was greater than 0.8 while NSR(Nitrification bacteria-Nitrospira sp.) gene and nitrate were related more than 0.9. A stabilization indicator(BOD/COD) and MTOT(Methane Oxidation bacteria), MCR(Methyl coenzyme M reductase), Dde(Dechloromonas denitrificans) genes were correlated over 0.8, but ferric iron and Fli(Ferribacterium limineticm) gene were at the lowest of 0.7. For MTOT, it was at the highest related at 100% over BOD/COD. In addition, anaerobic genes(i.e., nirS-Nitrite reductase, MCR. Dde, DSR) and DO were also related more than 0.8, which showing anaerobic reactions generally dependant upon DO. As demonstrated in the study, molecular biological investigation and water quality parameters are highly co-linked, so that quantitative real-time PCR could be cooperatively used for assessing landfill stabilization in association with the conventional monitoring parameters.