Titlebook: Image Analysis and Processing -- ICIAP 2011; 16th International C Giuseppe Maino,Gian Luca Foresti Conference proceedings 2011 Springer-Ver

商議

Cougar

Image De-noising by Bayesian Regressionn regression. This approach introduces an adaptive filter, well preserving edges and thin structures in the image. The hyper-parameters in the model as well as the predictive distribution functions are estimated through an efficient iterative scheme. We evaluate our method on common test images, con

verdict

A Rough-Fuzzy HSV Color Histogram for Image Segmentationmentation is performed by partitioning each block in multiple rough fuzzy sets that are used to build a lower and a upper histogram in the HSV color space. For each bin of the lower and upper histograms a measure, called . index, is computed to find the best segmentation of the image. Experimental r

解開

Multiple Region Categorization for Scenery Imagesues with global layout cues, following the statistical characteristics recently suggested in [1]. The observation that background regions in scenery images tend to horizontally span the image allows us to represent the contextual dependencies between background region labels with a simple graphical

改變立場

perpetual

Regions Segmentation from SAR Imagesion process presented consists in the evolution of an initial curve, including the interested region, until it reaches the boundary of the area to be extracted. The procedure proposed allows to obtain the same result of segmentation independently of the initial position of the curve. The results are

佛刊

delegate

假設(shè)

Uni-orthogonal Nonnegative Tucker Decomposition for Supervised Image Classificationhogonal factor matrices corresponding to each mode. Nonnegative Tucker Decomposition (NTD) model imposes nonnegativity constraints onto both core tensor and factor matrices. In this paper, we discuss a mixed version of the models, i.e. where one factor matrix is orthogonal and the remaining factor m

光亮

A Classification Approach with a Reject Option for Multi-label Problemstors and to attain a higher classification accuracy on automatically classified samples than the one which can be obtained without a reject option. Based on a recently proposed model of manual annotation time, we identify two approaches to implement a reject option, related to the two main manual an