![]() ![]() This standard deviation is a measure of image contrast, also known as “root mean square” (RMS) contrast. We will do this by first making the mean intensity to be zero and then alter the standard deviation to be 0.2. We will now adjust the histogram to make it be able to be preserved across our spatial filtering. That is, we will count up how many pixels have a particular intensity value for each of a range of intensities between -1 and 1. Let’s start by having a look at the intensity histogram of the image. For this lesson, we are going to use the image of UNSW shown below:įirst, however, we need to think about the intensity structure of the image.īecause we will be altering such structure during the filtering operations, we want to ensure that we a) preserve important properties of the image, and b) allow sufficient ‘room’ so that we don’t run into floor and ceiling issues (that is, intensities that are outside of the range that we can display).
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