Hierarchical data structures such as irregular pyramids are used by many applications related to image processing and segmentation. The construction scheme of such pyramids is bottom-up. Such a scheme forbids the definition of a level according to more global information defined at upper levels in the hierarchy. Moreover, the base of the pyramid has to encode any single pixel of the initial image in order to allow the definition of regions of any shape at higher levels. This last constraint raises major issues of memory usage and processing costs when irregular pyramids are applied to large images. The objective of this paper is to define a top-down construction scheme for irregular pyramids. Each level of such a pyramid is encoded by a combinatorial map associated to an explicit encoding of the geometry and the inclusion relationships of the corresponding partition. The resulting structure is a stack of finer and finer partitions obtained by successive splitting operations and is called a top-down pyramid.
Keywords: Segmentation; Irregular pyramid; Topological model; Combinatorial map;
Processing large images is a common issue in the computer vision framework with applications such as satellite or microscopic images. The major problem comes from the size of those images that prevents them from being loaded globally into memory. Moreover, such images contain different information at different levels of resolution. For example, global features, such as the delimitation of a tissue, appear at low resolution whereas finer details, such as cells, can only be distinguished at full resolution. Thus, the objective of this paper is the definition of a suitable hierarchical data structure that would provide full access to all the properties of the image by representing topological information. The idea consists in transposing the notion of tile for top-down topological pyramids to control accurately the amount of memory required by the construction of our model. As a result, this paper defines the topological model of tiled top-down pyramid and proposes a construction scheme that would not depend on the system memory limitations.
Keywords: Irregular pyramid; Topological model; Tiled data structure; Combinatorial map;
Applicative fields based on the analysis of large images must deal with two important problems. First, the size in memory of such images usually forbids a global image analysis hereby inducing numerous problems for the design of a global image partition. Second, due to the high resolution of such images, global features only appear at low resolutions and a single resolution analysis may loose important information. The tiled top-down pyramidal model has been designed to solve this two major challenges. This model provides a hierarchical encoding of the image at single or multiple resolutions using a top-down construction scheme. Moreover, the use of tiles bounds the amount of memory required by the model while allowing global image analysis. The main limitation of this model is the splitting step used to build one additional partition from the above level. Indeed, this step requires to temporary refine the split region up to the pixel level which entails high memory requirements and processing time. In this paper, we propose a new splitting step within the tiled top-down pyramidal framework which overcomes the previously mentioned limitations.
Keywords: Irregular pyramid; Topological model; Tiled data structure; Combinatorial map;
Recent microscopic imaging systems such as whole slide scanners provide very large (up to 18GB) high resolution images. Such amounts of memory raise major issues that prevent usual image representation models from being used. Moreover, using such high resolution images, global image features, such as tissues, does not clearly appear at full resolution. Such images contain thus different hierarchical information at different resolutions. This paper presents the model of tiled top-down pyramids which provides a framework to handle such images. This model encodes a hierarchy of partitions of large images defined at different resolutions. We also propose a generic construction scheme of such pyramids whose validity is evaluated on an histological image application.
Keywords: Irregular pyramid; Topological model; Combinatorial map;
This file was generated by bibtex2html 1.96.