Topic
Histogram equalization
About: Histogram equalization is a research topic. Over the lifetime, 5755 publications have been published within this topic receiving 89313 citations.
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TL;DR: Analysis of hardware experience with histogram projection explains why it produces intensity jitter in very low contrast scenes.
Abstract: The plateau equalization algorithm for display of IR images is defined to include histogram equalization and histogram projection as special cases. A maximum gain parameter is defined and surveyed for a large number of images, determining the useful range of plateau values. Analysis of hardware experience with histogram projection explains why it produces intensity jitter in very low contrast scenes. Detailed flow charts for hardware implementation of plateau equalization are provided.
128 citations
01 Dec 2011
TL;DR: The proposed Histogram Modified Local Contrast Enhancement (HM-LCE) provides optimum results by giving better contrast enhancement and preserving the local information of the original mammogram images in the Mias data base and the method has increased the detectability of micro calcifications present in the given mammogram image.
Abstract: Early detection of breast cancer in the mammograms is very essential in the field of medicine Contrast enhancement of mammograms based on Histogram Equalization (HE) is presented Histogram equalization is an effective and simple technique for contrast enhancement The standard histogram equalization (HE) usually results in excessive contrast enhancement because of lack of control on the level of enhancement The Histogram Modified Local Contrast Enhancement (HM-LCE) is introduced in this paper to adjust the level of contrast enhancement, which in turn gives the resultant image a strong contrast and also brings the local details present in the original image for more relevant interpretation It incorporates a two stage processing both histogram modifications as an optimization technique and a local contrast enhancement technique This method is tested for Mias mammogram images The performance of this method is determined using three parameters like Enhancement Measure (EME), Absolute Mean Brightness Error (AMBE) and Discrete Entropy (H) for all 22 numbers of Mias mammogram images with microcalcification It's enhancement potential is also tested by sobel and otsu methods for the detection of microcalcification in the mammogram image From the subjective and quantitative measures it is interesting that this proposed technique provides optimum results by giving better contrast enhancement and preserving the local information of the original mammogram images in the Mias data base and the method has increased the detectability of micro calcifications present in the given mammogram image
127 citations
TL;DR: A new indexing methodology for image databases integrating color and spatial information for content-based image retrieval, called Spatial-Chromatic Histogram (SCH), can be more satisfactory than standard techniques when the user would like to retrieve from the database the images that actually resemble the query image selected in their color distribution characteristics.
127 citations
TL;DR: A new algorithm for segmentation of SAR images based on threshold estimation using the histogram, which is applied to several RADARSAT SAR images with different number of looks.
127 citations
Journal Article•
TL;DR: The paper introduces the contrast sort methods, and introduces mainly the contrast limited adaptive histogram equalization, which enhance range by confining the height of local histogram, so limit noise magnification.
Abstract: The paper introduces the contrast sort methods,and introduces mainly the contrast limited adaptive histogram equalization,which enhance range by confining the height of local histogram,so limit noise magnification.
126 citations