Search results
Results from the WOW.Com Content Network
The contrast enhancement tries to change the intensity of the pixel in the image, particularly in the input image for the purpose to obtain a more enhanced image .It is based on the number of techniques namely local, global, dark and bright levels of contrast .The contrast enhancement is considered as the amount of color or gray differentiation ...
For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.
Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization in the respect that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image.
The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.
Luminance HDR/QtPfsGui is a free (open-source) HDR-workflow software for Linux, Windows and Mac OS X based around the pfstools package; LDR tonemapping is a free (open-source) tonemapper for low dynamic range images (a.k.a. "pseudo-HDR") Atlas is a free (open-source) port of the pfstmo tone mapping operators to Adobe After Effects
In image processing and photography, a color histogram is a representation of the distribution of colors in an image.For digital images, a color histogram represents the number of pixels that have colors in each of a fixed list of color ranges, that span the image's color space, the set of all possible colors.
Improvements in picture brightness and contrast can thus be obtained. In the field of computer vision, image histograms can be useful tools for thresholding. Because the information contained in the graph is a representation of pixel distribution as a function of tonal variation, image histograms can be analyzed for peaks and/or valleys.
If the images to be rectified are taken from camera pairs without geometric distortion, this calculation can easily be made with a linear transformation.X & Y rotation puts the images on the same plane, scaling makes the image frames be the same size and Z rotation & skew adjustments make the image pixel rows directly line up [citation needed].