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.
This paper presents a level of detail (LOD) selection algorithm for multi-resolution volume rendering using 3D texture mapping. It uses an adaptive scheme that renders the volume in a region-of-interest at a high reso...
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Based on the study of the characteristics of humans' vision system, this paper designed a new algorithm of medical image compression and combined the masking feature of human vision system and the three component ...
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Based on the study of the characteristics of humans' vision system, this paper designed a new algorithm of medical image compression and combined the masking feature of human vision system and the three component model of the image. The experiments were done on the medical images including CT and MRI. The results show that under the same compression ratio, the method used in the paper can achieve better subjective visual quality. The compression ratio can reach 16:1, if the visually lossless effect is required, i.e., almost all the relevant medical information is reserved.
In this paper, we propose a novel automatic object extraction algorithm, named the Template Guided Live Wire, based on the popularly used live-wire techniques. We discuss in details the novel method’s applications on...
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In this paper, we propose a novel automatic object extraction algorithm, named the Template Guided Live Wire, based on the popularly used live-wire techniques. We discuss in details the novel method’s applications on tongue extraction in digital images. With the guides of a given template curve which approximates the tongue’s shape, our method can finish the extraction of tongue without any human intervention. In the paper, we also discussed in details how the template guides the live wire, and why our method functions more effectively than other boundary based segmentation methods especially the snake algorithm. Experimental results on some tongue images are as well provided to show our method’s better accuracy and robustness than the snake algorithm.
Outliers are data values that lie away from the general cluster of other data values. Detecting the outliers of a dataset is an important research topic for data cleaning and finding new useful knowledge in many resea...
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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 ...
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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.
The aim of the present work is to assess the performance of three-dimensional Double Directional Filtering (TDDDF) algorithm for detecting and tracking a weak moving dim target against a complex cluttered background i...
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The aim of the present work is to assess the performance of three-dimensional Double Directional Filtering (TDDDF) algorithm for detecting and tracking a weak moving dim target against a complex cluttered background in infrared image sequences. This paper proposes an novel TDDDF to improve the integrated signal-to-clutter ratio (ISCR) and enhance the three-dimensional directional filter's (TDDF) target energy accumulation ability further. Since the TDDDF do well to whitening noise (or quasi whitening noise) but not so sensitive to complex cloudscene background, prior to the filtering, a newly pre-whitening method termed Spatial-Temporal Adaptive Filtering algorithm is used here to suppress clutter background. Extensive experiment results demonstrate the proposed algorithm's ability in detecting weak dim point target against cloud-cluttered background. Finally, performance comparisons of the proposed algorithm and TDDF, on real IR image data, are presented in which the advantages of the proposed TDDDF filters are shown.
The efficiency of an image compression technique relies on the capability of finding sparse M-terms for best approximation with reduced visually significant quality loss. By "visually significant" it is mean...
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This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of wea...
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This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of weather conditions and illumination changes. Furthermore, the achromaticity of the scene and the presence of occlusions in the tracking process are issues considered in the selection of the motion detector and tracking system respectively. We propose an adapted mixture of Gaussians model with RGB colour normalisation to detect mobile objects in the scene and a region tracking method based on significant mobile object features to track individuals and vehicles on the selected airport's apron. The performance of the proposed motion detector is evaluated using pixel-based performance metrics and compared with other existing methods. The capability of the application to handle partial occlusions is tested on the region tracker.
This paper proposed a novel watermarking scheme for the authentication of business documents by embedding a piece of information in the binary document image. Because it is based on printing text, the most important p...
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This paper proposed a novel watermarking scheme for the authentication of business documents by embedding a piece of information in the binary document image. Because it is based on printing text, the most important point is to find out an embedding and abstraction method based on the binary images. This paper gave out an embedding method based on the regions otherwise single pixels, in which the printing character is divided into some regions, and the watermark value is decided by the 0/1 ratio in the region. Based on many experiments, this paper also deduced the rules to change the 0/1 ratio without notice. At the end, the robustness of this method against hardware difference is experimented, and there-suits show that this scheme is useful and potential.
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