1,720,978 research outputs found
A Multiresolution Approach to Binary Tree Representations of Images
No full textA multiresolution method for constructing a BSP (binary space partitioning) tree is introduced. This approach derives a hierarchy (pyramid) of scale-space images from the original image. In this hierarchy, a BSP tree of an image is built from other trees representing low-resolution images of the pyramid. A low-resolution image BSP tree serves as an initial guess to construct a higher-resolution image tree. Due to filtering when constructing the pyramid, details are discarded. As a result, a more robust segmentation is obtained. Moreover a significant computational advantage is achieve
Image Compression Using Binary Partitioning Trees
No full textFor low bit-rate compression applications, segmentation-based coding methods provide, in general, high compression ratios when compared with traditional (e.g., ‘transform and subband) coding approaches. In this paper, we present a new segmentation-based image coding method that divides the desired image using binary space partitioning (BSP). The BSP approach partitions the desired image recursively by arbitrarily oriented lines in a hierarchical manner. This recursive partitioning generates a binary tree, which is referred to as the BSP-tree representation of the desired image. The most critical aspect of the BSP-tree method is the criterion used to select the partitioning lines of the BSP tree representation. In previous works, we developed novel methods for selecting the BSP-tree lines, and showed that the BSP approach provides efficient segmentation of images. In this paper, we describe a hierarchical approach for coding the partitioning lines of the BSP-tree representation. We also show that the image signal within the different regions (resulting from the recursive partitioning) can be represented using low-order polynomials. Furthermore, we employ an optimum pruning algorithm to minimize the bit rate of the BSP tree representation (for a ’given budget constraint) while minimizing distortion. Simulation results and comparisons with other compression methods are also presented
Fast Piecewise Constant Approximation of Images
No full textIn this work, we present a Least-Square-Error (LSE), recursive method for generating piecewise-constant approximations of images. The method is developed using an optimization approach to minimize a cost function. The cost function, proposed here, is based on segmenting the image, recursively, using Binary Space Partitionings (BSPs) of the image domain. We derive a LSE necessary condition for the optimum piecewise-constant approximation, and use this condition to develop an algorithm for generating the LSE, BSP-based approximation. The proposed algorithm provides a significant reduction in the computational expense when compared with a brute force method. As shown in the paper, the LSE algorithm generates efficient segmentations of simple as well as complex images. This shows the potential of the LSE approximation approach for image coding applications. Moreover, the BSP-based segmentation provides a very simple (yet flexible) description of the regions resulting from the partitioning. This makes the proposed approximation method useful for performing image affine transformations (e.g., rotation and scaling) which are common in computer graphics applications
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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