Browsing by Author "Chang, DC"

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Adaptive filter bank reconstruction using fast multichannel RLS algorithms
(1998-06-11)
Chang, DC
;
Wu, WR
;
電信工程研究所
;
Institute of Communications Engineering
The recursive least-squares (RLS) algorithm has been used in the adaptive synthesis filter bank for fast convergence. However, because of interpolation operations involved in the synthesis process, fast RLS algorithms cannot be applied. In this Letter, an approach is proposed that can formulate subband reconstruction as a multichannel filtering problem. This formulation allows the application of fast multichannel RLS algorithms and substantial reduction in computational complexity.
An efficient architecture of ultrasonic scan conversion for implementing the cubic convolution interpolation
(1998)
Chang, DC
;
Wu, WR
;
Jeng, JH
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電信工程研究所
;
Institute of Communications Engineering
The nearest neighbor and the bilinear interpolation methods are widely adopted to perform ultrasonic scan conversion in commercial ultrasound systems. The reason is that they are easy to implement and can satisfy real-time requirement. As the hardware technology advances in the recent decade, more complex yet more eligible interpolation methods can be realized. However, few articles in the literature concern details about the reconstruction of ultrasonic images. In this paper we propose an efficient architecture of ultrasonic scan conversion for implementing the cubic convolution interpolation. Some parameters needed to calculate in interpolation processes can be previously designed in ROMs (Read Only Memory) to improve computational efficiency. The system requirement analysis and computer simulations have shown the appealing feasibility in real-time practice and superior reconstruction quality to conventional interpolation methods.
Comments on "Maneuvering target tracking with colored noise" - Author's reply
(1998-04-01)
Wu, WR
;
Chang, DC
;
電信工程研究所
;
Institute of Communications Engineering
Feedback median filter for robust preprocessing of glint noise
(2000-10-01)
Chang, DC
;
Wu, WR
;
電信工程研究所
;
Institute of Communications Engineering
Glint noise may arise in a target tracking system. The non-Gaussian behavior of glint noise can severely degrade the tracking performance, Measurement preprocessing at the front-end of the tracker is an effective method to reduce glint noise. The preprocessor proposed by Hewer, Martin, and Zeh, which used the computationally intensive M-estimator, may not be suitable for practical implementation. An alternative method employing the median filter is studied here. The median tilter is well known for its simplicity and robustness. However, the efficiency of the median biter can be seriously degraded if input samples are not identically distributed. This is what we may encounter in the tracking problem. A feedback median filter is then proposed to overcome this impediment without substantially increasing complexity. Simulations show that the new preprocessor can greatly improve tracking performance in the glint noise environment.
Image contrast enhancement based on a histogram transformation of local standard deviation
(1998-08-01)
Chang, DC
;
Wu, WR
;
電信工程研究所
;
Institute of Communications Engineering
The adaptive contrast enhancement (ACE) algorithm, which uses contrast gains (CG's) to adjust the high-frequency components of images, is a well-known technique for medical image processing. Conventionally, the CG is either a constant or inversely proportional to the local standard deviation (LSD), However, it is known that conventional approaches entail noise overenhancement and ringing artifacts, In this paper, we present a new ACE algorithm that eliminates these problems. First, a mathematical model for the LSD distribution is proposed by extending Hunt's image model. Then, the CG is formulated as a function of the LSD. The function, which is nonlinear, is determined by the transformation between the LSD histogram and a desired LSD distribution. Using our formulation, it can be shown that conventional ACE's use linear functions to compute the new CG's, It is the proposed nonlinear function that produces an adequate CG resulting in little noise overenhancement and fewer ringing artifacts. Finally, simulations using some X-ray images are provided to demonstrate the effectiveness of our new algorithm.
Image contrast enhancement based on a local standard deviation model
(1997)
Chang, DC
;
Wu, WR
;
交大名義發表
;
電信工程研究所
;
National Chiao Tung University
The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt's Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm.
Maneuvering target tracking with colored noise
(1996-10-01)
Wu, WR
;
Chang, DC
;
交大名義發表
;
電信工程研究所
;
National Chiao Tung University
It is known that colored noise may degrade the performance of a tracking algorithm. A common remedy is to model colored noise as an autoregressive (AR) process and apply the measurement difference method One problem with the approach is that the AR parameters are usually unknown. In this work, we propose a new method to adaptively estimate the AR parameters. It is shown that this method is simple and practically feasible. We incorporate our method into the interacting multiple model (IMM) tracking algorithm and show that the performance is almost as good as that in the known parameters case.