A novel Parallel-Based Lifting Algorithm （PBLA） for Discrete Wavelet Transform （DWT）, exploiting the parallelism of arithmetic operations in all lifting steps, is proposed in this paper. It leads to reduce the cri...
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A novel Parallel-Based Lifting Algorithm （PBLA） for Discrete Wavelet Transform （DWT）, exploiting the parallelism of arithmetic operations in all lifting steps, is proposed in this paper. It leads to reduce the critical path latency of computation, and to reduce the complexity of hardware implementation as well. The detailed derivation on the proposed algorithm, as well as the resulting Very Large Scale Integration （VLSI） architecture, is introduced, taking the 9/7 DWT as an example but without loss of generality. In comparison with the Conventional Lifting Algorithm Based Implementation （ClabI）, the critical path latency of the proposed architecture is reduced by more than half from （4Tm ＋ 8Ta）to Tm ＋ 4Ta, and is competitive to that of Convolution-Based Implementation （CBI）, but the new implementation will save significantly in hardware. The experimental results demonstrate that the proposed architecture has good performance in both increasing working frequency and reducing area.
Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation k...
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Walsh-Haar function system that was first intruoduced by us is a new kind of function systems, and has a good global/local property. This function system is called Walsh ordering function system since its generation kernel functions belong to Walsh ordering Walsh function system. We worked out a recursive property of the matrix WHKRm+1 corresponding to the first KR m+1 Walsh-Haar functions in Walsh-Haar function system, and we also proved that Walsh-Haar function system is perfect and orthogonal similar to Walsh function system and Haar function system. Thus, discrete Walsh-Haar transformation (DW-HT) is an orthogonal transformation that can be widely used in signal processing. In this paper, using the recursive property of the matrix WHKRm+1 and the fast algorithm of discrete Walsh transformation (DWT) in Walsh ordering, we have designed a fast algorithm of Walsh ordering DW-HT based on the bisection technique. The idea and method used in this paper can be used for designing fast algorithms of other ordering DW-HTs and other discrete orthogonal transformations.
Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection...
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Target detection techniques play an important role in automatic target recognition (ATR) systems because overall ATR performance depends closely on detection results. In this paper, a novel method for fusion detection of infrared weak targets based on multifeature distance map (MFDM) in image sequences is proposed. As for small weak targets, there are many features, such as local entropy, average gradient strength. These features depict the characteristics of small infrared targets and can be extracted. Multifeature-based fusion techniques are applied to detect such weak targets. The problem of detecting small targets is converted to search peak values in specified feature space where multifeature vectors space (MFVS) is considered. Distance map (DM) can be derived according to feature vectors and target detection is performed in DM. In order to accumulate energy of targets deeply and suppress background and clutters to a great extent, five distance maps obtained by corresponding five consecutive frames are utilized to fuse with average weight, which results in the fact that the contrast between targets and background including clutters are enlarged and that the feature peaks of targets are obvious different from background and clutters. After these steps, a contrast segmentation method is used to extract targets from complicated background on the fused DM. Actual infrared image sequences in background of sea and sky are applied to validate the proposed approach. Experimental results demonstrate the robustness of the proposed method with high performance.
To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability...
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To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.
A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applie...
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A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applied to estimate a new diffusion coefficient. Experimental results demonstrate that anisotropic diffusion based on this new erosion operator can efficiently reduce noise and sharpen object boundaries.
A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applie...
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A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applied to estimate a new diffusion coefficient. Experimental results demonstrate that anisotropic diffusion based on this new erosion operator can efficiently reduce noise and sharpen object boundaries.
作者：
吴伟仁田玉龙黄翔宇Institute for Pattern Recognition and Artificial Intelligence
State Key Lab. for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Deep Space Exploration Research Center
Harbin Institute of Technology Harbin 150001 Chinahe image elements of earth-center and moon-center are obtained by processing the images of earth and moon these image elements in combination with the inertial attitude information and the moon ephemeris are utilized to obtain the probe initial position relative to earth and the Levenberg-Marquardt algorithm is used to determine the accurate probe position relative to earth and the probe orbit relative to earth is estimated by using the extended Kalman filter. The autonomous optical navigation algorithm is validated using the digital simulation.
The image elements of earth-center and moon-center are obtained by processing the images of earthand moon, these image elements in combination with the inertial attitude information and the moon ephemerisare utilized ...
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The image elements of earth-center and moon-center are obtained by processing the images of earthand moon, these image elements in combination with the inertial attitude information and the moon ephemerisare utilized to obtain the probe initial position relative to earth, and the Levenberg-Marquardt algorithm is usedto determine the accurate probe position relative to earth, and the probe orbit relative to earth is estimated by u-sing the extended Kalman filter. The autonomous optical navigation algorithm is validated using the digital simu-lation.
作者：
王振华吴伟仁田玉龙田金文柳健Institute for Pattern Recognition and Artificial Intelligence
State Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and Technology Wuhan 430074 China Institute for Pattern Recognition and Artificial Intelligence
State Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and Technology Wuhan 430074 China major limitation for deep space communication is the limited bandwidths available. The downlink rate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However the Next Generation Space Telescope (NGST) will produce about 600 GB/d. Clearly the volume of data to downlink must be reduced by at least a factor of 100. One of the resolutions is to encode the data using very low bit rate image compression techniques. An very low bit rate image compression method based on region of interest(ROI) has been proposed for deep space image. The conventional image compression algorithms which encode the original data without any data analysis can maintain very good details and haven't high compression rate while the modern image compressions with semantic organization can have high compression rate even to be hundred and can't maintain too much details. The algorithms based on region of interest inheriting from the two previews algorithms have good semantic features and high fidelity and is therefore suitable for applications at a low bit rate. The proposed method extracts the region of interest by texture analysis after wavelet transform and gains optimal local quality with bit rate control. The Result shows that our method can maintain more details in ROI than general image compression algorithm(SPIHT) under the condition of sacrificing the quality of other uninterested areas
A major limitation for deep space communication is the limited bandwidths available. The downlinkrate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However, the Next GenerationSpace Telescop...
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A major limitation for deep space communication is the limited bandwidths available. The downlinkrate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However, the Next GenerationSpace Telescope (NGST) will produce about 600 GB/d. Clearly the volume of data to downlink must be re-duced by at least a factor of 100. One of the resolutions is to encode the data using very low bit rate image com-pression techniques. An very low bit rate image compression method based on region of interest(ROI) has beenproposed for deep space image. The conventional image compression algorithms which encode the original datawithout any data analysis can maintain very good details and haven' t high compression rate while the modernimage compressions with semantic organization can have high compression rate even to be hundred and can' tmaintain too much details. The algorithms based on region of interest inheriting from the two previews algorithmshave good semantic features and high fidelity, and is therefore suitable for applications at a low bit rate. Theproposed method extracts the region of interest by texture analysis after wavelet transform and gains optimal localquality with bit rate control. The Result shows that our method can maintain more details in ROI than generalimage compression algorithm(SPIHT) under the condition of sacrificing the quality of other uninterested areas.
With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction...
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