1,721,136 research outputs found
Adaptive Split for Image Coding
No full textThe purpose of this paper is to present an adaptive split procedure for decomposing an image into a set of squares of different size and its application to image coding. The sub-image contained in each square is approximated in the least mean square sense using polynomial functions. Different algorithms have been established in order to use the separability condition when the approximation is evaluated on a rectangular grid. Starting with a certain set of identical size squares covering the image, the approximation is calculated for each of them. Then, different measurements are performed in order to determine the quality of the approximation inside each square. Whenever this quality is not sufficient, the analysed square is split into four sub-squares of identical size. The same procedure is integrated until the quality is considered good enough. In order to enhance the quality, special smoothing is finally applied on the boundary of big size squares. Examples present the coding efficiency of this type of processing
Recent Results in High Compression Image Coding
No full textThe digital representation of an image requires a very large number of bits. The goal of image coding is to reduce this number as much as possible, and to reconstruct a faithful duplicate of the original picture. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau of about 10:1 several years ago. Recent progress in the study of the brain mechanism of vision and of scene analysis has opened new vistas in picture coding. The concept of directional sensitivity of neurones in the visual cortex combined with the separate processing of contours and textures has led to a new class of coding methods, called second generation, capable of achieving compression ratios as high as 100:1. In this paper, recent results on object-based coding methods are reported, exhibiting improvements in the previous second-generation methods
Fuzzy Segmentation of Multiple Articulated Elliptical Curves from Sparse Contour Data
No full textIn this paper a method is presented for estimating the parameters of a composite object consisting of several "primitive" objects, that undergo rigid transformations. The objects are fitted to the features that are extracted from the data images. The physical relations between the sub-objects are exploited as constraints on the solution space of the resulting optimisation problem. Particular attention in this paper is given to the segmentation problem. This partitioning of the feature data is performed by a fuzzy segmentation, which is integrated within the framework of the parameter estimation problem. An important feature of the method is that no attempt is made to establish closed-form relations. Instead, bounds on the parameters and on the constraints allow adapting the optimisation to the uncertainty in the data and to the knowledge available a priori. The power of the method is that it can accomodate different primitive curves and constraints with the same general structure Application of the method is in the field of human motion estimation where each of part of the body is modelled by a separate geometric object. The method is illustrate with results on both artificially generated and real feature data
Adaptive Split-and-Merge for Image Analysis and Coding
No full textAn approximation algorithm for two-dimensional (2-D) signals, e.g. images, is presented. This approximation is obtained by partitioning the original signal into adjacent regions with each region being approximated in the least square sense by a 2-D analytical function. The segmentation procedure is controlled iteratively to insure at each step the best possible quality between the original image and the segmented one. The segmentation is based on two successive steps: splitting the original picture into adjacent squares of different size, then merging them in an optimal way into the final region configuration. Some results are presented when the approximation is performed by polynomial functions
Constrained Composite Curve Fitting for Human Body Modelling
No full textZuerich, Switzerland. Ade F., Ed
Symmetry-Based Image Coding
No full textA novel coding technique which proposes the use of symmetry to reduce redundancy in images is presented. Axes of symmetry are extracted using the Principal Axes of Inertia theory and the technique is extended to non-symmetric images by the introduction of a Coefficient of Symmetry. One part of the images is then linearly predicted with respect to the chosen axis. The method is implemented in a block-based fashion in order to adapt to local symmetries on the image data. An image representation and a coding strategy is illustrated, and results are presented on real static images
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