The number of images and the settings in which images may be captured is ever increasing. For example, users have ready access to an image capture device in a variety of different settings through inclusion on mobile phones, tablet computers, and so on.
Because of the variety in settings, however, the images may become corrupted, e.g., noisy. This corruption may be due to limitations of the setting (e.g., low light, dusty) and even due to limitations of the image capture device itself, e.g., limitations in capturing motion, resolution, sensitivity, and so forth. Consequently, this corruption may interfere with a user's enjoyment of the actual image itself.
Although techniques have been developed to process the image to remove this corruption, at least partially, these techniques may be resource intensive and thus limited in the amount of functionality that may be made available to a user. Other image processing techniques may also suffer from similar limitations due to the amount of resources used to perform the techniques.