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.
A novel reconfigurable hardware system which uses both multi-DSP and FPGA to attain high performance and real-time imageprocessing are presented. The system structure and working principle of mainly processing multi-...
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A novel reconfigurable hardware system which uses both multi-DSP and FPGA to attain high performance and real-time imageprocessing are presented. The system structure and working principle of mainly processing multi-DSP 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 *** it is suitable for real-time imageprocessing and can get satisfactory effect of image recognition.
This paper presents an effective method to detect small and dim infrared image target under complex background, which is performed in spatial domain. Roughly speaking, the new method contains two steps. The first step...
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ISBN:
(纸本)0819460079
This paper presents an effective method to detect small and dim infrared image target under complex background, which is performed in spatial domain. Roughly speaking, the new method contains two steps. The first step is further divided into two steps (called difference between maximum and minimum filters, DMMFs): firstly, an original image is filtered by maximum (max) and minimum (min) filters based on the considering max filter can enhance the target and preserve the background while min filter can eliminate the target and also preserve the background;and then the difference between these two results is obtained, therefore the target is enhanced and its background is suppressed at the same time. To obtain an accurate location of the target, the second step called post processing involves local feature mapping and projecting techniques. This DMMF method focuses on reducing the cost of computation, tracking the target in real-time, enhancing the SNR, and suppressing its background clutter. The simulation results show that the proposed algorithm is effective and practical.
Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no ge...
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Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image would be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical.
Synthetic Aperture Radar (SAR) image compression is important in image transmission and archiving. We present a new algorithm for SAR image compression based on projection pursuit neural networks. At first, we segment...
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ISBN:
(纸本)3540259139
Synthetic Aperture Radar (SAR) image compression is important in image transmission and archiving. We present a new algorithm for SAR image compression based on projection pursuit neural networks. At first, we segment an SAR image into regions of different sizes based on mean value in each region and then constructing a distinct code for each block by using the projection pursuit neural networks. The process is stopped when the desired error threshold is achieved. The experimental results show that excellent performance can be achieved for typical SAR images with no significant distortion introduced by image compression.
In this paper, we propose a new method integrating both a priori shape information and our knowledge about gray levels of the desired structure. We describe an approach inspired from tracking to deal with non-uniform ...
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ISBN:
(纸本)0889865183
In this paper, we propose a new method integrating both a priori shape information and our knowledge about gray levels of the desired structure. We describe an approach inspired from tracking to deal with non-uniform gray levels. We define focus region to consider both interior and exterior of the desired object. We utilize signed distance function to consider shape information. Embedding a priori shape and gray level knowledge in a statistical platform, we use correlation between changes in shape and histogram to improve the results. Our method successfully segments Thalamus and other brain structures.
Fuzzy cluster analysis (FCA) of functional magnetic resonance images, suffers from some drawbacks such as a priori definition of number of clusters and unidentified statistical significance of results. Here, we introd...
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ISBN:
(纸本)0889865183
Fuzzy cluster analysis (FCA) of functional magnetic resonance images, suffers from some drawbacks such as a priori definition of number of clusters and unidentified statistical significance of results. Here, we introduce a method to control the rate of false positive detection in FCA which gives a meaningful statistical significance to the results. Using this method, we also derive the optimal number of clusters. In this study by measuring the rate of false alarm detection while analyzing 6 experimental datasets, we evaluate the introduced method for making statistical inference.
Because of poor signal-to-noise ratio (SNR) of the fMRI time series and confounding effects, the results of fMRI analysis are often unsatisfactory. Existence of significant noise and artifacts in fMRI time-series as w...
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ISBN:
(纸本)0889865183
Because of poor signal-to-noise ratio (SNR) of the fMRI time series and confounding effects, the results of fMRI analysis are often unsatisfactory. Existence of significant noise and artifacts in fMRI time-series as well as their unknown structure, complicates the problem of activation detection in the time domain. This makes the fMRI noise suppression a challenging problem. Based on some assumptions, different parametric denoising methods such as wavelet based denoising methods have been introduced in the literature. But these assumptions may not necessarily hold for the fMRI data. To remedy this problem, using randomization analysis, we propose a novel wavelet-based denoising method for fMRI analysis. The proposed denoising method is employed to build a feature space for fMRI cluster analysis and its efficiency is shown using simulated and experimental datasets.
A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmissio...
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A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmission connections can switch smoothly among the multiple proxies by maint aining a coherent connection *** mechanism is transparent to application programs and can support th e building of *** the cooperation of some other security components,the mechanism guarantees the reso urce availability and reliability of the end system against some attacks to the specific ports or hosts.
A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,in which the security-demanded transmission...
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A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,in which the security-demanded transmission connections can switch smoothly among the multiple proxies by maintaining a coherent connection context. The mechanism is transparent to application programs and can support the building of VPN. With the cooperation of some other security components,the mechanism guarantees the resource availability and reliability of the end system against some attacks to the specific ports or hosts.
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