Recently in my digital photography class I learned about HDR pictures. Specifically how to combine pictures with different exposure values to create a picture similar to what your eye sees. I admit, I never thought the same ideas would apply in a research paper I read for my Computer Science senior design class. Instead of combining pictures to get all the detail from multiple exposure values, the paper discusses getting a high resolution picture using a collection of low-resolution pictures. The idea is pretty much the same though. Since each picture will have different pixels with good information, you take the good information from each picture and add it to the final product. This seems like a fairly intuitive approach to the topic. However, the technique is not without it's obstacles. You see, in photography you don't always get the exact same picture when you press the button a second time. Something in the scene might change. For example, your angle to the object might be different ever so slightly. The background might change or move, especially if there are creatures in the background. A direct merge of these pictures would result in very messy final picture. Not exactly the "super resolution" you're looking for.
The paper is actually about addressing this obstacle. They approach the problem understanding there may be subtle differences in the different picture, and bring in the idea of error. They create a curve based upon all the pictures and then assign error weights based upon how far the value of a pixel is from the curve. The farther the pixel value is, the smaller weight it has. The assigned weights are based upon an outlier threshold determined at the creation of the curve. These weights allow for the final picture to partially ignore, or even exclude irrelevant information from the final picture. The results of this method are a crisp picture that exclude extra data, including extra objects that may be placed in one of the contributing pictures.
Source:
El-Yamany, N. A., & Papamichalis, P. E. (2008).
Robust Color Image Superresolution:. Journal on Image and Video Processing
- Color in Image and Video Processing , 1-12.
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