# A Review of Oil Spill Remote Sensing
## 3 Use of Active Sensors for Oil Spill Detection and Mapping
### Radar Image Processing  
There are many spill look-alikes which interfere with radar imagery. Many studies have been devoted to removing the look-alikes from radar imagery [44]. Further, there are other aberrations to oil spill mapping by radar. Extensive efforts have been devoted to automating this interference-elimination process and radar data processing in general. The data processing steps generally follow a procedure which will be outlined here. An important first process is to assess the particular image for quality [45]. If the image meets certain quality requirements, then it will be advanced for further processing. The next step then becomes removal of noise and speckle. Noise is contained in many radar images. Noise can complicate subsequent analysis and therefore should be reduced [46]. Speckle is a special kind of granular noise. Speckle noise results from constructive and destructive interference of the signal shown as bright and dark dots in the image. The presence of speckle may negate further processing. There are several methods to remove speckle, one of which is to average several images of the same area over time [47].  
The next step in radar image processing is the removal of wind fields and fixed geographic features. Radar detection of oil is difficult or impossible in low or high wind areas. It is then imperative to compare radar imagery to the wind field for that area [48]. One method of dealing with winds is to use a wind map of same scale as the radar image for direct comparison.  
Land and near-shore areas constitute an interference to radar detection of oil spills. Processing of radar imagery alongside a graphical information systems (GIS) can eliminate these no-oil-detect areas such as areas close to shore [46]. Similarly known weed beds or other interferences can be blanked out.  
The third step in radar processing is to locate the oil \"dark\" spots in the image with the highest accuracy. Edge detection is an imagery processing method which find the distinct boundary between the target feature and background [49]. Several mathematical algorithms have been developed for edge detection in radar images. Texture analysis is a technique to distinguish the area surface characteristic of imagery and has been applied to radar imagery of oil [50]. Oil generally shows a consistent texture, whereas sea has a rougher texture. Another way to approach the detection of the black oil areas is to use shape analysis. Oil shows different shapes compared to look-alikes. These differences have been used to differentiate oil from look-alikes [51; 52].  
Intelligent systems are often used to assist in image processing, sometimes including the above steps. The basic procedure involves manual input into a system that follows the steps and then uses this \"learning\" to perform the process by computerized procedures [53; 54; 55]. Development of these techniques has now lead to several systems that are automatic or semi-automatic and can interpret a radar image for oil slicks in a matter of minutes. Algorithms for radar interpretation are also available to subscribed users on the internet. This vast improvement has occurred in the past 10 years.