Added small remark about depth image.

Author: golanlevin

chapters/image_processing_computer_vision/chapter.md

@@ -75,7 +75,7 @@ In openFrameworks, raster images can come from a wide variety of sources, includ
 - perhaps more exotically, a *depth image*, in which pixel values represent *distances* instead of colors. Depth images can be captured from real-world scenes with special cameras (such as a Microsoft Kinect via the `ofxKinect` addon), or extracted from synthetic CGI scenes using (for example) `ofFBO::getDepthTexture()`.
 
 ![We don't have the rights to this image, it's just something I found on the internet. We need something similar](images/kinect_depth_image.png) 
-*An example of a depth image (left) and a corresponding RGB color image (right), captured simultaneously with a Microsoft Kinect. In the depth image, the brightness of a pixel represents its proximity to the camera.*
+*An example of a depth image (left) and a corresponding RGB color image (right), captured simultaneously with a Microsoft Kinect. In the depth image, the brightness of a pixel represents its proximity to the camera. (Note that these two images, presented in a raw state, are not yet "calibrated" to each other, meaning that there is not an exact pixel-for-pixel correspondence between a pixel's color and its corresponding depth.)*
 
 Incidentally, OF makes it easy to **load images directly from the Internet**, by using a URL as the filename argument, as in `myImage.loadImage("http://en.wikipedia.org/wiki/File:Example.jpg");`. Keep in mind that doing this will load the remotely-stored image *synchronously*, meaning your program will "block" (or freeze) while it waits for all of the data to download from the web. For an improved user experience, you can also load Internet images *asynchronously* (in a background thread), using the response provided by `ofLoadURLAsync()`; a  sample implementation of this can be found in the openFrameworks *imageLoaderWebExample* graphics example. Now that you can load images stored on the Internet, you can fetch images *computationally* using fun APIs (like those of [Temboo](https://temboo.com/library/), [Instagram](http://instagram.com/developer/) or [Flickr](https://www.flickr.com/services/api/)), or from dynamic online sources such as live traffic cameras.