Radial basis function (RBF) neural network can be used as a universal approximator. In this paper, we propose a novel method to apply RBF net to reconstruct 2-dimensional computerized tomography (CT) images from a sma...
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ISBN:
(纸本)1424406048
Radial basis function (RBF) neural network can be used as a universal approximator. In this paper, we propose a novel method to apply RBF net to reconstruct 2-dimensional computerized tomography (CT) images from a small amount of projection data. In the method, the cross-sectional image is represented by a RBF network, the unknown cross-sectional image vector is replaced by the function of the network's weight vector. As proved by us, the line integral of the weight matrix can be calculated providing the projections of the CT image are known. The ART method can be employed to obtain the final reconstructed CT image. Experiments show that the proposed method can obtain the better reconstructed image than the filtered back projection (FBP), and it is also more efficient than ART method alone
This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display...
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This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display of equivalent pixel curves at the part of pathological changes and display of breast tumor image edge. Accordingly, three feature extraction operators are proposed, i.e. the combination operators of anisotropic gradient and smoothing operator, an improved Sobel operator and an edge sharpening operator. Furthermore, quantitative diagnostic approaches are discussed based on blood and oxygen contents according to abundant clinical data and pathological mechanism of breast tumors. The results of clinic show that the methods of combining qualitative and quantitative diagnose are effective for breast tumor images, especially for early and potential breast cancer
To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave an...
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To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast thresholding. The experimental results show that the method using fractal dimension to fuse dualband infrared images, and then detect targets is superior to use mid-wave or long -wave infrared images detect targets alone.
A C64x-based multi-DSP real-time imageprocessing system is introduced, which uses high performance TMS320C6414 DSP to process image and FPGA device to realize LINK port to transport image data with LVDS signal. Requi...
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A C64x-based multi-DSP real-time imageprocessing system is introduced, which uses high performance TMS320C6414 DSP to process image and FPGA device to realize LINK port to transport image data with LVDS signal. Requirements of imageprocessing performance and image data communication of image fusion are met. Based on the hardware system, a real time microkernel based distributed operating system is designed and implemented. At the end, its real-time performance is analyzed from three aspects. It's shown that the real time imageprocessing system can reach the requirements of real time imageprocessing.
Since the DC-coupled interface between the driver and the laser diode makes it impossible for the conventional drivers to work with low power supply, an output stage has been proposed. A novel APC can suppress the out...
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Since the DC-coupled interface between the driver and the laser diode makes it impossible for the conventional drivers to work with low power supply, an output stage has been proposed. A novel APC can suppress the output average optical power and extinction ratio within ±0.3 dBm and ±0.4 dB(-40°C to 100°C), respectively. The initialization time is not more than 0.6 μs because the fast binary search algorithm is incorporated into the APC. The burst-on delay and burst-off delay are less than 5 ns and meet the requirement of PON system. The chip is fabricated in TSMC 0.8 μm BiCMOS process and occupies an area of 1.56 mm × 1.67 mm with a power consumption of 105 mW.
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.
A novel reconfigurable hardware system which uses both muhi-DSP and FPGA to attain high performance and real-time imageprocessing are presented. The system structure and working principle of mainly processing multi-B...
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A novel reconfigurable hardware system which uses both muhi-DSP and FPGA to attain high performance and real-time imageprocessing are presented. The system structure and working principle of mainly processing multi-BSP board, extended multi-DSP board are analysed. The outstanding advantage is that the communication among different board components of this system is supported by high speed link ports ＆ serial ports for increasing the system performance and computational power. Then the implementation of embedded real-time operating systems （RTOS） by us is discussed in detail. In this system, we adopt two kinds of parallel structures controlled by RTOS for parallel processing of algorithms. The experimental results show that exploitive period of the system is short, and maintenance convenient. Thus it is suitable for real-time imageprocessing and can get satisfactory effect of imagerecognition.
Open-dose by reconstruction is one of the most important algorithms in mathematical morphology, it was used widely in image and video processing, but it requires the huge computational power, what is the bottleneck fo...
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Open-dose by reconstruction is one of the most important algorithms in mathematical morphology, it was used widely in image and video processing, but it requires the huge computational power, what is the bottleneck for application. So in this paper, Cellular Neural Network (CNN) is used to solve the problem, new +1 template and "and" template are designed here, along with the already developed templates and image preprocessing technique, the gray-scale open-close by reconstruction is realized. Experimental results based on CNN simulator are shown, proved that the speed on CNN is about 300 times faster than in traditional PC, the real time processing can be realized.
Radar scene matching technique has been widely found in many application fields such as remote sensing, navigation, terrain-map match, scenery variance analysis and so on. Radar image geometry is quite different from ...
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Radar scene matching technique has been widely found in many application fields such as remote sensing, navigation, terrain-map match, scenery variance analysis and so on. Radar image geometry is quite different from that of optical satellite imagery, whose imaging is a slanting imaging of electromagnetic microwave reflection. The different characters between radar image and optical satellite images are very distinct, such as the layover distortion of ground-truth and speckle noise, which degrades the image to such an extent that the features are very unclear and difficult to be extracted. So the factors such as the hypsography, ground truth, sensor altitude and imaging time should be taken into account for radar image and optical image matching. In this paper, we develop an image match algorithm based on reference map multi-area selection using fuzzy sets. image matching is generally a procedure that calculates the similarity measurement between sensed image and the corresponding intercepted image in reference map and it searches the maximum position in the correlation map. Our method adopts a converse matching strategy which selects multi-areas in optical reference map using fuzzy sets as model images, then match them on the sensed image respectively by normalized cross correlation matching algorithm and fuse the match results to get the optimum registered position. Multi-areas selection mainly considers two influence factors such as ground-truth texture features and the hypsography (DEM) of imaging region, which will suppress the influence of great variance imaging region. Experiment results show the method is effective in registering performance and reducing the calculation.
When an monocular vision-based unmanned aerial vehicle (UAV) based on vision is flown to the final approach fix to intercept the glide slope without the navigation of Global Positioning System (GPS), the position and ...
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When an monocular vision-based unmanned aerial vehicle (UAV) based on vision is flown to the final approach fix to intercept the glide slope without the navigation of Global Positioning System (GPS), the position and orientation of the airport runway in image must be detected accurately so as to a host of suitable procedures have to be followed. The optimum length of the final approach is about five miles from the runway threshold. The front view of the runway, which is achieved at the moment, is very illegible. The approaching marking (cross bar) of the runway are showed as some white spots of high intensity and the complicated backgrounds of the airport are included in the images. In this case, spots with high intensity should be extracted and classified, some of these spots are just the images of the background noises and the pseudo-targets, which can't be separated with the spots of the runway as in the view there is no significant characteristic difference among them ostensibly. Fortunately, in the terrestrial coordinate space, most of the runway marks are located at the apexes of a rectangle, having some geometric relationships. The relationship among the projection coordinates of the runway spots in the images can be determined according to the perspective principle, the constraint condition of the rectangle as well as the front shot constraint condition of the target, by using this relationship, the runway approaching marks can be separated, the position and the direction of the runway in the images can be identified. In this paper, the clustering management is adopted so as to greatly reduce the computing time. The consequence of the experiments shows that by this algorithm, even from a place far away from the runway whose marks are unclear, we also can effectively detect the runway.
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