Efficient edge operators such as those based on partial derivatives fail to return continuous edge maps. To address this, a supplementary edge linking step is required to complete initial edge information. In this pap...
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Efficient edge operators such as those based on partial derivatives fail to return continuous edge maps. To address this, a supplementary edge linking step is required to complete initial edge information. In this paper we. propose a fast and efficient algorithm for edge linking using local information around edge terminators. In order to minimize incorrect linking decisions, the direction and the linking path for each edge terminator are established by minimizing a cost function. The particular novelty of this approach lies in the labeling scheme which assigns the directionality of the. edge terminators (endpoints) based only on local knowledge. As a consequence, it relaxes the demand of a priori knowledge and furthermore assures an accurate and efficient search for edge paths in the image. (C) 2002 SPIE and IST.
As we approach the new millenium, error diffusion is approaching the 25th anniversary of its invention. Because elf its exceptionally high image quality, it continues to be a popular choice among digital halftoning al...
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As we approach the new millenium, error diffusion is approaching the 25th anniversary of its invention. Because elf its exceptionally high image quality, it continues to be a popular choice among digital halftoning algorithms. Over the fast 24 years, many attempts have been made to modify and improve the algorithm-to eliminate unwanted textures and to extend if to printing media and color Some of these modifications have been very successful and are in use today. This paper will review the history of the algorithm and ifs modifications. Three watershed events in the development of error diffusion will be described, together with the lessons learned along the way. (C) 1999 SPIE and IS&T.
In this paper, we make a comparative study on morphological skeletonization (MSK) and fuzzy medial axis transformation (FMAT), Methods have been proposed to construct convex FMAT from the morphological skeleton points...
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In this paper, we make a comparative study on morphological skeletonization (MSK) and fuzzy medial axis transformation (FMAT), Methods have been proposed to construct convex FMAT from the morphological skeleton points and to translate FMAT to MSK respectively. For the case of translating MSK to convex FMAT the experimental results reveal that the combination of the proposed method and the redundant removal algorithm is very effective. Especially, the combined method is faster than the original method for constructing convex FMAT of smoothed images. (C) 2002 SPIE and IST.
We describe a texture description algorithm, designed in the wavelets domain, to reduce the dimension of an existing texture-based feature vector and improve on the existing texture description algorithm in terms of b...
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We describe a texture description algorithm, designed in the wavelets domain, to reduce the dimension of an existing texture-based feature vector and improve on the existing texture description algorithm in terms of both effectiveness and efficiency. We first demonstrate that the estimated texture directions at different wavelet decomposition scales are very similar. Thus, a new texture description with explicit direction representation can be constructed to improve discrimination capability. Second, we propose a subband integration scheme to further improve the texture description and achieve robustness to rotation of texture patterns. Third, a range of successful texture description elements developed in the pixel domain are applied to the LL subband and added to the texture descriptor for further enhancement of the proposed algorithm. Extensive testing, benchmarked by the existing techniques, shows that the proposed algorithm not only reduces the sensitivity of retrieval to image texture rotation, but also improves the retrieval accuracy. c (c) 2006 SPIE and IS&T.
This article introduces a new algorithm to detect active fires in geostationary remotely sensed data. The algorithm calculated dynamic statistical multispectral thresholds based on, and sensitive to, biogeographical r...
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This article introduces a new algorithm to detect active fires in geostationary remotely sensed data. The algorithm calculated dynamic statistical multispectral thresholds based on, and sensitive to, biogeographical region, subseason, and time-of-day. The spectral characteristics of nonfire and noncloud mid-infrared values were found to vary with biogeographical region, subseason, and time-of-day. These differences were exploited to define a new seasonal Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) multivariate adaptive threshold geostationary satellite fire anomaly algorithm. The algorithm was demonstrated on 12 months of daytime data acquired from the geostationary satellite system, the Advanced Himawari Imager (on Himawari-8) over Australia (7.69 million km(2)). The resulting hotspots were compared with those from the existing Moderate Resolution Imaging Spectrometer (MODIS) polar-orbiting fire-hotspot algorithm. The intercomparison showed that BRIGHT wildfire hotspots, detected using Himawari-8 and Interim Biogeographic Regionalisation of Australia (IBRA) data, were also detected by MODIS polar-orbiting fire hotspots 88% of the time. While MODIS hotspots were detected by BRIGHT hotspots only 39% of the time;the majority of the undetected MODIS hotspots had low radiative power. BRIGHT provides a new method for the remote sensing of active fires providing reliable observations at spatial and temporal scales useful for fire managers.
There is an urgent need to extract key information automatically from video for the purposes of indexing, fast retrieval, and scene analysis. To support this vision, reliable scene change detection algorithms must be ...
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There is an urgent need to extract key information automatically from video for the purposes of indexing, fast retrieval, and scene analysis. To support this vision, reliable scene change detection algorithms must be developed. This paper describes a novel algorithm for wipe scene change detection in uncompressed and MPEG-1 compressed video sequences using statistical and geometric properties of each image. An efficient algorithm is also proposed to estimate statistical features in compressed video without full frame decompression. From uncompressed and MPEG compressed frames, thumbnails are obtained where pixels are the averages and variances of luminance values of macroblocks. Differences between thumbnails are computed and thresholded, and straight lines are detected in the resulting binary images. Persistence and motion of these lines indicate the presence of a shot transition using wipes. Results on video of various content types are reported and validated with the proposed schemes. Furthermore, results show that the accuracy of the detection is above 95% for uncompressed and above 90% for MPEG-1 compressed video. (C) 2004 SPIE and IST.
We present two new techniques for reducing blocking artifacts in motion compensated frames. These techniques can be applied generally to motion compensated frames obtained by employing any partitioning schemes. In the...
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We present two new techniques for reducing blocking artifacts in motion compensated frames. These techniques can be applied generally to motion compensated frames obtained by employing any partitioning schemes. In the first technique, the weighting coefficients of the overlapped block motion compensation are modeled with fuzzy relations. These fuzzy relations are formed based on two fuzzy sets, which define the closeness of a given pixel to the block boundaries in the horizontal and vertical directions, respectively. The second technique uses the similarity between a set of pixels inside a partitioned region and that on the borders to modify the border pixels. Simulations conducted on several benchmark video sequences indicate that the proposed techniques can improve the subjective quality of the frames as well as reduce the prediction error. (c) 2006 SPIE and IS&T.
A constant false alarm rate (CFAR) detection algorithm and a threshold selection algorithm are adapted and developed for use in multiband-image small-target detection. While it is often difficult to predict the spectr...
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A constant false alarm rate (CFAR) detection algorithm and a threshold selection algorithm are adapted and developed for use in multiband-image small-target detection. While it is often difficult to predict the spectral signatures of targets, the shape of the target may be known. This detection algorithm exploits geometric target features and spectral differences between the target and the surrounding area. The detection algorithm is derived from a general statistical model of the data with most emphasis on the background. The utility of CFAR algorithms is that the selection of a detection threshold can be made independently of image intensity. However, varied applications of the algorithms show that detection values are dependent on the scene adherence to the model. Achieving a CFAR in applications is very difficult. The threshold for a desired number of false alarms fluctuates with differing backgrounds. By appropriately mapping observations to the model, an automatic threshold selection algorithm is shown. Combining the CFAR-detection algorithm with the threshold selection algorithm produces a reliable constant false alarm rate. (c) 2005 SPIE and IS&T.
We propose a direct image segmentation algorithm in the JPEG compressed domain. The algorithm features extracting statistical parameters from direct cosine transform (DCT) coefficients without its inverse transform, a...
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We propose a direct image segmentation algorithm in the JPEG compressed domain. The algorithm features extracting statistical parameters from direct cosine transform (DCT) coefficients without its inverse transform, and growing regions in line with JPEG compression seamlessly in blocks of 8 x 8 pixels. In comparison with the latest research efforts in region-based image segmentation, our proposed algorithm achieves significant advantages, including (1) no iteration is involved, (2) no full decompression is required, and (3) segmentation performance is competitive. (C) 2003 SPIE and IST.
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