Contrast enhancement plays a fundamental role in image processing. Many histogram-based techniques are widely used for contrast enhancement of given images, due to their simple function and effectiveness. However, the conventional histogram equalization (HE) methods result in excessive contrast enhancement, which causes natural looking and satisfactory results for a variety of low contrast imag...

In this project, six histogram-based search methods are investigated in two different color spaces, RGB and HSV. Histogram search characterizes an image by its color distribution, or histogram but the drawback of a global histogram representation is that information about object location, shape, and texture is discarded. Thus this project showed that images retrieved by using the global color h...

Histogram equalization (HE) is one of the common methods for improving contrast in digital images. However, HE may introduce some unnecessary visual deterioration while enhancing image. One of the solutions to overcome this weakness is by preserving the mean brightness of the output image. This paper proposes a new method, known as dynamic contrast enhancement using multiple and clipped histogr...

We propose a method for fast extraction of sphere. Basically, main algorithms of the extraction in 3D figure are the same as 2D method we reported in previous research. The proposed method utilizes the one-dimensional histogram as search space, and the polytope method which is one of the minimization algorithms for search parameters in target figure. The histogram has two characteristics: (a) T...

We present two efficient histogram algorithms designed for NVIDIA’s compute unified device architecture (CUDA) compatible graphics processor units (GPUs). Our algorithm can be used for parallel computation of histograms on large data-sets and for thousands of bins. Traditionally histogram computation has been difficult and inefficient on the GPU. This often means that GPU-based implementation o...

Histogram equalization is one of the common tools for improving contrast in digital photography, remote sensing, medical imaging, and scientific visualization. It is a process for recovering lost contrast in an image by remapping the brightness values in such a way that equalizes or more evenly distributes its brightness values. However, Histogram Equalization may significantly change the brigh...

Abstract Mutual Information (MI) is an important dependency measure between random variables, due to its tight connection with information theory. It has numerous applications, both in theory and practice. However, when employed in practice, it is often necessary to estimate the MI from available data. There are several methods to approximate the MI, but arguably one of the simplest and most wi...

In this paper, a method for enhancing low contrast images is proposed. This method, called Gaussian Mixture Model based Contrast Enhancement (GMMCE), brings into play the Gaussian mixture modeling of histograms to model the content of the images. Based on the fact that each homogeneous area in natural images has a Gaussian-shaped histogram, it decomposes the narrow histogram of low contrast ima...

Enhancing an image in such a way that maintains image edges is a difficult problem. Many current methods for image enhancement either smooth edges on a small scale while improving contrast on a global scale or enhance edges on a large scale while amplifying noise on a small scale. Many applications of histograms for the purposes of image processing are well known. However, applying this process...

OBJECTIVE Our aim was to figure out whether volumetric gray-scale histogram difference between anterior and posterior cervix can indicate the extent of cervical consistency. METHODS We collected data of 95 patients who were appropriate for vaginal delivery with 36th to 37th weeks of gestational age from September 2010 to October 2011 in the Department of Obstetrics and Gynecology, Korea Unive...