Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexin...
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Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexing, as well as embedded boundary data extension technique, is adopted to optimize the design of the architecture. These reduce significantly the required numbers of the multipliers, adders and registers, as well as the amount of accessing external memory, and lead to decrease efficiently the hardware cost and power consumption of the design. The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately. Experimental simulation and comparison results are presented, which demonstrate that the proposed architecture has lower hardware complexity, thus it is adapted for embedded applications. The presented architecture is simple, regular and scalable, and well suited for VLSI implementation.
Efficient line-based very large scale integration architectures for the 2-D discrete wavelet transform (DWT) based on a lifting scheme, using the 9/7 wavelet filters adopted in the JPEG 2000 proposal, are proposed. Th...
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Efficient line-based very large scale integration architectures for the 2-D discrete wavelet transform (DWT) based on a lifting scheme, using the 9/7 wavelet filters adopted in the JPEG 2000 proposal, are proposed. The embedded decimation technique based on folding and time multiplexing was exploited to optimize the architecture, which reduces the size of buffer memory required and the amount of RAM access, and hence the occupied area and power consumption of the devices. Using this technique, a single-input, single-output architecture (SISOA) and a two-input, two-output architecture (TITOA) are proposed. The presented SISOA is designed to generate one output per clock cycle;the TITOA is designed to generate two outputs per clock cycle with the same memory requirement as that for SISOA, where the four sub-band coefficients of the transformed signal are available interleaved. Because only one line of data is required at a time, a single-port memory can be used. Performance analysis and comparison results demonstrate that the proposed method is economical of hardware cost and computation time. The advantages of the design also include short output latency, simple data flow, regularity, and scalability, as well as suitability for VLSI implementation. (c) 2006 Society of Photo-Optical Instrumentation Engineers.
An integrated burst-mode laser diode driver is presented for PON application. The bias current range and modulation current range are 1-75 mA and 5-80 mA respectively. The DC-coupled interface between the driver and t...
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An integrated burst-mode laser diode driver is presented for PON application. The bias current range and modulation current range are 1-75 mA and 5-80 mA respectively. The DC-coupled interface between the driver and the laser diode can tolerate the output transient voltage as low as 0.6v. The novel digital APC loop can stabilize the output average optical power and extinction ratio respectively within +/- 0.3 dBm and +/- 0.4 dB (-40 to 100 degrees C) with less than 0.6 mu s initialization time and infinite bias current and modulation current hold time. Moreover, the fast burst response is achieved with burst on/off time less than 5 ns. The chip is implemented in a TSMC 0.35-mu m SiGe BiCMOS technology and occupies an area of 1.56 x 1.67 mm(2) with power consumption of 105 mW from a supply voltage of 2.5 v.
Localization and labeling of function regions in brain is an important topic in experimental brain sciences because the huge amount of data collected by neuroscientists will become meaningless if we cannot give them a...
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ISBN:
(纸本)0819461849
Localization and labeling of function regions in brain is an important topic in experimental brain sciences because the huge amount of data collected by neuroscientists will become meaningless if we cannot give them a precise description of their locations. In this paper, we proposed a localization and labelling method of 3D MR image of rat brain based on Paxinos-Watson atlas. Our objective is to use the specific atlas to accomplish localization and labeling of specified tissue of interest (TOI) to mimic a veteran expert such that invisible or unclear anatomic function regions in the MR images of rat brain can be automatically identified and marked. We proposed a multi-step method to locate and label the TOIs from the MR image of rat brain. Firstly, preprocessing. It alms at the digitization and 3D reconstruction of the atlas and MRI of rat brain. Secondly, two-step registration. The global registration is to eliminate the big misalign and section angle offset as well as the scale between the MRI and atlas. We can choose some unambiguous and characteristic points manually, and based on these correspondences a coarse registration is obtained using affine model. The local registration is to address individual variability of rat brain that can be performed by using Snake model. Thirdly, post-processing. The goal is to locate and label the TOIs in the selected MR image of rat brain slice guided by well-registered atlas. The experiments demonstrated the feasibility of our method.
DSP/FPGA-based parallel architecture oriented to real-time imageprocessing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnecti...
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Efficient line-based architectures for two-dimensional discrete wavelet transform (2-D DWT) are presented in this paper. We first present a four-input/four-output architecture for direct 2-D DWT that 1-level decomposi...
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Efficient line-based architectures for two-dimensional discrete wavelet transform (2-D DWT) are presented in this paper. We first present a four-input/four-output architecture for direct 2-D DWT that 1-level decomposition of a N x N image could be performed in approximately N-2/4 intra-working clock cycles (ccs), where the parallelism among four subbands transforms in lifting-based 2-D DWT is explored. By using this four-input/four-output architecture, we propose a novel pipelined architecture for multilevel 2-D DWT that can perform a complete dyadic decomposition of N x N image in approximately N-2/4 ccs. Performance analysis and comparison results demonstrate that, the proposed architectures have faster throughput rate and good performance in terms of production of throughput rate and hardware cost, as well as hardware utilization. The proposed pipelined architecture could be an efficient alternative for high-speed and/or low-power applications.
Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature select...
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Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.
作者:
Sun, Yu-QiuTian, Jin-WenLiu, JianYangtze Univ
Sch Informat & Math Jinzhou 434023 Peoples R China Huazhong Univ Sci & Technol
Inst Pattern Recognit & Artificial Intelligence State Educ Commiss Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol
Dept Elect Informat & Energy State Educ Commiss Key Lab Image Proc & Intelligent Control Wuhan Peoples R China
Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selectes and the approach used. Feature level fusion i...
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ISBN:
(纸本)1424400600
Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selectes and the approach used. Feature level fusion is a potential and difficult fusion level. Bayesian fusion method is an important theory in feature level. A new method is presented to fuse infrared images and recognize object in the paper. Firstly, Bayesian principles, fusion mode and recognition decision function are described. Then, aiming at the features of mid-wave infrared image and long-wave infrared image, we use Bayesian probability to fuse them. Last, recognize target and background obtained with training and test pattern vectors. The experiment results show stability and feasibility of the fusion recognition using Bayesian decision theory in infrared image.
In this paper, we develop a method for the reconstruction of 3D coronary artery based on two perspective projections acquired on a standard single plane angiographic system in the same systole. Our reconstruction is b...
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ISBN:
(纸本)0819464236
In this paper, we develop a method for the reconstruction of 3D coronary artery based on two perspective projections acquired on a standard single plane angiographic system in the same systole. Our reconstruction is based on the model of generalized cylinders, which are generated by sweeping a two-dimensional cross section along an axis in three-dimensional space. We restrict the cross section to be circular and always perpendicular to the tangent of the axis. Firstly, the vascular centerlines of the X-ray angiography images on both projections are semiautomatically extracted by multiscale vessel tracking using Gabor filters, and the radius of the coronary are also acquired simultaneously. Secondly, the relative geometry of the two projections is determined by the gantry information and 2D matching is realized through the epipolar geometry and the consistency of the vessels. Thirdly, we determine the three-dimensional (3D) coordinates of the identified object points from the image coordinates of the matched points and the calculated imaging system geometry. Finally, we link the consequent cross sections which are processed according to the radius and the direction information to obtain the 3D structure of the artery. The proposed 3D reconstruction method is validated on real data and is shown to perform robustly and accurately in the presence of noise.
<正>The image fusion is an important approach to produce a single complete image which preserves all relevant information from different *** this paper,we proposed a support value transform-based multi focus image f...
<正>The image fusion is an important approach to produce a single complete image which preserves all relevant information from different *** this paper,we proposed a support value transform-based multi focus image fusion method,where the fused saliency features are represented by support values. Based on the mapped least squares support vector machine,the support value transform is developed as a multi-scale analysis *** fusing results on the multi focus images demonstrate that the proposed image fusion method is effective and efficient.
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