29-11-2012, 03:53 PM
Virtual Reality
Virtual Reality.ppt (Size: 413 KB / Downloads: 78)
Intensity Histogram
In an image processing context, the histogram of an image normally refers to a histogram of the pixel intensity values. This histogram is a graph showing the number of pixels in an image at each different intensity value found in that image. For an 8-bit greyscale image there are 256 different possible intensities, and so the histogram will graphically display 256 numbers showing the distribution of pixels amongst those greyscale values.
The operation is very simple. The image is scanned in a single pass and a running count of the number of pixels found at each intensity value is kept. This is then used to construct a suitable histogram.
Contrast Stretching
Its histogram, shows that most of the pixels have rather high intensity values. Contrast stretching the image yields which has a clearly improved contrast, the corresponding histogram is .
Histogram Equalization
is another image with low contrast. However, if we look at its histogram, , we see that the entire intensity range is used and we therefore cannot apply contrast stretching. On the other hand, the histogram also shows that most of the pixels values are clustered in a rather small area, whereas the top half of the intensity values is used by only a few pixels.
Contrast Stretching
Before the stretching can be performed it is necessary to specify the upper and lower pixel value limits over which the image is to be normalized. Often these limits will just be the minimum and maximum pixel values that the image type concerned allows. e.g. for 8-bit greylevel images the lower and upper limits might be 0 and 255. Call the lower and the upper limit a and b respectively.