An image contrast enhancement algorithm based on discriminant analysis is presented in this paper. An automatic adaptive segmentation algorithm, based on discriminant analysis, is utilized to segment the gray-values of an image into several clusters. After the adaptive segmentation algorithm, different object components of the image are segmented into separate clusters, called object planes. Th...

Color histogram matching has been shown to be a promising way of quickly indexing into a large image database. Yet, few experiments have been done to test the method on truly large databases, and even if they were performed, they would give little guidance to a user wondering if the technique would be useful with his or her database. In this paper we de ne and analyze measures relevant to exten...

We propose a secure steganographic approach with a high capacity. We first use small neighborhoods of the original histogram to calculate the minimum remapping from a histogram to the odd-only and even-only histograms. We then employ a quantization index modulation-based odd-even embedding to preserve the histogram of each embedding subchannel. A minimum distortion remapping policy is used to d...

An approach to image mining is described that combines a histogram based representation with a time series analysis technique. More specifically a Dynamic Time Warping (DTW) approach is applied to histogram represented image sets that have been enhanced using CLAHE and noise removal. The focus of the work is the screening (classification) of retinal image sets to identify age-related macular de...

Abstract. Histograms are commonly used for representing summaries of observed data and they can be considered non parametric estimates of probability distributions. Symbolic Data Analysis formalized the concept of histogram symbolic variable, as a variable which allows to describe statistical units by histograms instead of single values. In this paper we present a linear regression model for mu...

Image segmentation is a basic work in the field of image analysis and computer vision. Thresholding is one of the simplest methods of image segmentation. In general, thresholding approaches based on 1-D histogram do not make use of any space adjacent information of the image, thus it is often ruined by noise; thus, thresholding methods based on 2-D histogram are put forward. These methods have ...

In this paper, a general framework for image contrast enhancement algorithm based on an optimization problem is presented. Through this optimization, the intensities can be better distributed. The algorithm is based on the facts that the histogram of the enhanced image is close to the input image histogram and uniform distribution, simultaneously. Based on this fact, we obtain a closed form opt...

BACKGROUND Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MR...