Histogram equalization

About: Histogram equalization is a research topic. Over the lifetime, 5755 publications have been published within this topic receiving 89313 citations.

Color Palette Generation

Abstract: A method of extracting a color palette includes receiving initial color attribute values of corresponding image elements representing an image, transforming the initial color attribute values to lexical color classifiers of the corresponding image elements, clustering the image elements based on the lexical color classifiers into clusters of image elements, and generating a color palette having color regions, each color region corresponding to a color associated with a cluster of image elements.

Optimized recognition pretreatment method for human face

Abstract: The invention relates to an optimized human face recognition preprocessing method. The method comprises the following steps: firstly, converting a color human face image from a camera into a gray level image, then performing a scale normalization processing on the gray level image to cause the human face images to have the same size and posture, dividing the human face images into low-frequency components and high-frequency components by wavelet transformation, performing a histogram equalization processing on the low-frequency components only, executing wavelet reconstruction on the processed low-frequency components and the high-frequency components, and finally processing the reconstructed images by optimized median filtering. The method has the advantages of regulating the gray level range of the human face images, enhancing the contrast, better improving the human face gray level images with higher brightness, and enhancing the human face identification efficiency in a complicated illumination environment with different postures.

Adjusting method and device with high dynamic range

Abstract: The invention discloses an adjusting method with high dynamic range which comprises the following steps: obtaining the brightness range of images with low dynamic range according to the brightness of the images with high dynamic range, wherein the brightness range of the images with low dynamic range is the brightness range which can be displayed by a display device; and conducting linear mapping and histogram equalization on obtained results of the brightness range of the images with low dynamic range, and obtaining the images with low dynamic range. In the invention, high dynamic range adjustment technology for global mapping of single-frame images is more reasonable so as to improve the image quality, the details of bright and dark environments can be reasonably displayed simultaneously, algorithm is simple and practical, and discontinuous brightness caused by the fusion of local mapping and multi-frame images is avoided; and by providing users with the factors for controlling the image contrast and detail richness, the images are convenient for being adjusted to the effect which is more acceptable for human eyes.

Image comparison using color histograms

Abstract: Methods, apparatus and articles of manufacture for image comparison using color histograms are disclosed. An example method disclosed herein to compare a first image and a second image comprises obtaining a first color histogram for a first set of pixels sampled from the first image, obtaining a second color histogram for a second set of pixels sampled from the second image, determining a comparison metric based on differences between bin values of the first color histogram and adjusted bin values of the second color histogram, and determining whether the first image and the second image match based on the comparison metric.

Change detection using joint intensity histogram

Abstract: In the present paper, a method for detecting changes between two images of the same scene taken at different times using their joint intensity histogram is proposed. First, the joint histogram, which is a two-dimensional (2D) histogram of combinatorial intensity levels, (I1(x), I2 (x)), is calculated. By checking the characteristics of the ridges of clusters on the joint histogram, clusters that are expected to correspond to background are selected. The combinations of (I1, I2) covered by the clusters are determined as insignificant changes. Pixels having a different combinatorial intensity (I1(x), I2 (x)) from these combinations, are extracted as candidates for significant changes. Based on the gradient correlation between the images for each region consisting of these pixels, only regions with significant changes are distinguished. Experiments using real scenes show the practical usefulness of the method