Update index.md (#196)

Improves the introductory documentation of the ImageCore.jl package

Co-authored-by: Ashwani Rathee <[email protected]>
Co-authored-by: Tim Holy <[email protected]>

docs/src/index.md

@@ -7,6 +7,23 @@ representations through different "view" types, and to provide some
 useful low-level functions (including "traits") that simplify image
 display, input/output, and the writing of algorithms.
 
+Some of the key features and functionalities provided by ImageCore.jl include:
+
+- Storage type transformations: ImageCore.jl provides various methods like `float32`, `n0f8`, etc which can be used to transform raw storage type of the image without changing the color space. 
+- Image view conversion: It provides various methods like `rawview`, `channelview`, `colorview` , `stackedview` which help in conversions between various types of representations. Default representation of images is likely all that is needed most of the time but these functions provided more flexibility while working with image data.
+- Pixel level transformations: Several methods like `clamp01` , `clamp01nan`, `scaleminmax`, etc are available that help with truncating image pixel values within certain valid limits and helps to avoid IO errors.
+- Image Traits: These can prove to be useful to users when trying to add more meaning to different axes of image and to add dimension specific information.
+
+
+ImageCore often acts as the "common core" dependency for working with any kind of image in the JuliaImages ecosystem, but itself provides almost none of the standard image-processing algorithms. These algorithms are found in other packages in the JuliaImages ecosystem.
+
+If you want to use ImageCore.jl, you can add it to your project environment using the package manager. Open a Julia REPL and use the following command:
+
+```jl
+] add ImageCore
+```
+
+
 If you're just getting started with images in Julia, it's recommended
 that you see the
 [introductory documentation](http://juliaimages.github.io/latest/). In