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  Effects of Atmosphere on digital Image processing: Hello everyone, and welcome to our new discussion which is on atmospheric errors and corrections under this remote sensing essential course. Earlier we briefly touched on this issue and but today we are going to discuss in depth the reasons for atmospheric distortions and then how these are reflected in our satellite images finally we will also see what are the  possibilities of getting rid of atmospheric distortions.  So as you know that you know between satellites and earth surface there is atmosphere. But if the atmosphere is very thin or would have been thin then there should have been a delight for RCO or for any need remote sensing people. But unfortunately, it is not true in the case of earth and though it is very important for life, it is fine. But if we think about mars, then mars is having a very thin atmosphere. And therefore though it is written here the geologist delight but does not mean only for geologist...

Histogram-Based Enhancements The histogram is a graphical representation that brings a visual impression of the distribution of data. Rather  than looking just at digital numbers, which becomes difficult to understand how the pixel values are  distributed against an image. But if we plot a histogram, which is easy to do, on the y-axis we get the frequency on the x-axis we get the pixel value. And once it  is done, then a lot of information as also discussed in previous lectures can be gathered about a particular  image. So histograms provide a basically univariate because histograms of individual bands, individual  images there, that is why it is univariate. And if we want to see the histogram of 2, then it would be bivariate  or multivariate or also possible. So one variable description of data, how data is distributed and that tells  also how the quality of an image taken by a sensor, so that can be seen An image histogram is basically  which is...