HSV is one of the color space transforms that separate color from intensity. Depending on your application (my understanding is contrast enhancement is somehow related to image segmentation in your OP), there are several advantages of HSV:

1. Histogram equalization of a color image is suggested only on the intensity component;

2. The Saturation component is regarded as invariant in shadow (only intensity changes), so processing the image in HSV space is better suit for shadow removing. [This post][1] that tried to remove the shadow from an image is for your reference;

3. The Hue component makes the algorithm better immune and thus more robust to lighting variations. This feature makes it better fit in some medical applications such as the palm skin segmentation (under normal RGB space it is not easy to thresholding out the hand palm).

4. In color enhancement that you mentioned, if the colors in your image are not so strong, it would be quite difficult to detect colored objects. Adding some arbitrary value in the Image would not Help, since it would increase the brightness but not the contrast. After the conversion to HSV space you may increase the Saturation then convert it back to the RGB color space. The colors of interest may appear much better in the image which would facilitate the object recognition nicely. You can have a try by this means to adjust your image contrast.


 
You may also want to check [this post][2] for more discussions.


  [1]: https://stackoverflow.com/questions/20331347/how-to-remove-shadow-of-image-on-matlab/20333646#20333646
  [2]: https://dsp.stackexchange.com/questions/2687/why-do-we-use-the-hsv-colour-space-so-often-in-vision-and-image-processing