PNNL

Abstract

We describe a unique approach to image resolution enhancement, inverse kriging (IK), which takes advantage of the spatial relationship between high- and low-resolution images within an area of overlap. Once established, this mathematical relationship then can be applied across the entire low-resolution image to significantly sharpen the image. The mathematical relationship uses the spatial correlations within the low-resolution image and between the low and high spatial-resolution imagery. Two of the most important requirements of the technique are that the images be co-registered well within the resolution of the larger pixels and that the spatial structure of the training area (where the spatial correlation statistics are compared) is similar to the structure of the remaining image area where it will be applied. Testing was performed using same-sensor and multi-sensor imagery. We show results that indicate that the method does improve the low spatial-resolution imagery. The selection of a training area spatial structure similar to the area being processed is important, as areas with different spatial structure (e.g., vegetation versus buildings and roads) will produce poor results. Comparisons with bilinear interpolation demonstrate that IK could be used as an improved interpolation tool, for example, in the image-registration process.