04-06-2012, 11:03 AM
Spatial Domain Methods – Histogram Processing
Histogram Processing.ppt (Size: 546.5 KB / Downloads: 31)
Histogram Processing:
The histogram of a digital image with gray levels in the range [0,L-1] is a discrete function h[rk] = nk, where rk is the kth gray level and nk is the number of pixels in the image having gray level rk.
The normalized histogram is obtained by dividing each of its values by the total no. of pixels in the image, denoted as ‘n’.
Thus a normalized histogram is given by p(rr) = nk/n, for k = 0, 1, ….., L-1. i.e., p(rr) gives an estimate of the probability of occurrence of gray level rr.
The sum of all components of a normalized histogram is ‘1’.
Histogram manipulation can be used effectively for image enhancement.
In addition to providing useful image statistics, the information inherent in histograms also is useful in other image processing applications, such as, image compression and segmentation.
It is a popular tool for real time image processing.
Summary:
The spatial domain – histogram processing and its applications are studied.
Histogram equalization is discussed.