Search results
Results From The WOW.Com Content Network
Histogram equalization is a method in image processing of contrast adjustment using the image's histogram. Histograms of an image before and after equalization.
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.
An example of histogram matching. In image processing, histogram matching or histogram specification is the transformation of an image so that its histogram matches a specified histogram. [1] The well-known histogram equalization method is a special case in which the specified histogram is uniformly distributed. [2]
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
Multi-block LBP: the image is divided into many blocks, a LBP histogram is calculated for every block and concatenated as the final histogram. Volume Local Binary Pattern(VLBP): [11] VLBP looks at dynamic texture as a set of volumes in the (X,Y,T) space where X and Y denote the spatial coordinates and T denotes the frame index. The neighborhood ...
In image processing, the balanced histogram thresholding method (BHT), [1] is a very simple method used for automatic image thresholding.Like Otsu's Method [2] and the Iterative Selection Thresholding Method, [3] this is a histogram based thresholding method.
In image processing, normalization is a process that changes the range of pixel intensity values. Applications include photographs with poor contrast due to glare, for example.
Histogram equalization is a popular example of these algorithms. 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 ...