Color histograms are widely used for content-based image retrieval. Their advantages are efficiency, and insensitivity to small changes in camera viewpoint. However, a histogram is a coarse characterization of an image, and so images with very different appearances can have similar histograms. We describe a technique for comparing images called histogram refinement, which imposes additional con...

Histogram equalization is an efficient contrast enhancement algorithm. Global equalization is effective, but enhances only overall contrast, while local histogram equalization is more powerful, but computationally expensive. In this paper, a Block-based Binomial Filtered Histogram Equalization (BBFHE) algorithm is presented. The image is divided into blocks, and for each block a histogram is ob...

A novel algorithm for image segmentation based on adaptive thresholding of the global histogram of an image is proposed and applied to medical images from the medical database of the Second Department of Surgery of the University Hospital of Alexandroupolis, Greece. The threshold values are specified through an adaptive process that determines the optimum number of histogram regions and, at the...

Content-based image retrieval (CBIR) is a collection of techniques for retrieving images on the basis of features, such as color, texture and shape. An efficient tool, which is widely used in CBIR, is that of color image histograms. The classic method of color histogram creation results in very large histograms with large variations between neighboring bins. Thus, small changes in the image mig...

This paper presents the first application of spatially correlated neutral models to the detection of changes in mortality rates across space and time using the local Moran's I statistic. Sequential Gaussian simulation is used to generate realizations of the spatial distribution of mortality rates under increasingly stringent conditions: 1) reproduction of the sample histogram, 2) reproduction o...