SAR images are corrupted by a special noise phenomenon called speckle which makes information extraction from the images difficult. The project will identify appropriate techniques, existing as well as new, to reduce the speckle and these techniques will be analysed theoretically, implemented and the performance evaluated.
A SAR (Synthetic Aperture Radar) is an airborne or spaceborne radar, and it acquires images of the surface of the Earth with very good spatial resolution (i.e. down to a few meters). The SAR uses an advanced processing technique to obtain the good resolution. A large number of applications exist within different topics: monitoring of sea ice in the Greenland Sea, monitoring of agricultural crops, determination of soil moisture on fields, determination of biomass and other vegetation parameters for crops and trees, topographic mapping, and mapping of glaciers and the inland ice in Greenland. The SAR images contain other types of information than conventional image data from, e.g. visible and infrared sensors, because the radar operates at microwave frequencies, where other characteristics of the surface (e.g. water content in plants or the soil, and the structure of the plants) control the appearance of the objects in the images. Furthermore, the radar images are independent of sun light and cloud cover, in contrast to the visible and infrared images.
The advanced processing technique used in the SAR requires a coherent signal to obtain the good spatial resolution. Unfortunately, in addition this causes a special “noise” phenomenon called speckle for distributed targets, such as agricultural fields, forest areas, and sea ice floes. Within a resolution cell individual scatterers, e.g. stalks, fruit, leaves, branches, and surface facets, reflect the radar signal. These reflections may interfere constructively or destructively, and thereby causing the resulting signal for the resolution cell to vary strongly from cell to cell. The speckle may cause problems for standard image processing methods because the speckle is not Gaussian distributed. The problem of reducing the speckle may be approached in two ways, either as a filtering problem or as an estimation problem, where the task is to estimate the underlying backscatter coefficient. The simplest technique used for speckle filtering is simple averaging, but the disadvantage is that the spatial resolution is also reduced. Therefore, a number of so-called adaptive filters has been suggested in the literature to reduce the speckle without reducing the spatial resolution. In the project existing algorithms for speckle reduction will be analyzed and evaluated, and it will be possible to propose new and refined filters.
The project will start with a literature review to seek information about existing speckle reduction techniques. Hereafter, appropriate techniques, existing as well as new, will be identified, analysed theoretically, implemented and the performance evaluated.
Statistics and experience with programming