In the field of remote sensing, aerial and/or satellite images of terrain are studied to determine information about the land that is imaged. For example, in the forest products industry, aerial or satellite images of timberlands are used because the lands are often too vast or remote to access and survey on foot. The images of the timberlands may be analyzed to determine such information as the boundaries of a forest, the age of the trees in the forest, the types of trees in the forest, and a variety of other information.
In some cases, digital, aerial, or satellite images of terrain will contain missing pixel data. For example, a well-publicized mechanical failure on the Landsat 7 satellite causes images to be produced with bands of missing pixel data. Similarly, the terrain depicted in an aerial or satellite image may be fully or partially obscured by clouds, shadows, or other phenomena, thereby making it difficult to analyze.
Most commonly, images with missing pixel data or data that does not show what is desired are corrected with pixel duplication techniques whereby the pixel data to be filled in or replaced are obtained from the image itself and are assumed to be similar to the data for neighboring good pixels. However, such techniques often produce poorly-corrected images. Therefore, there is a need for a technique that can fill in missing pixel data and/or replace pixel data that produces a better approximation of how the underlying object or terrain in an image actually appears.