Intelligent ocean oil spill detection method for remote sensing large image

[0037] Such as figure 1 As shown in Fig. 1, geometric correction and noise filtering are performed on the input SAR image, and then sea and land segmentation is performed to shield the land influence; then, for the whole scene image, the approximate position of the oil slick is monitored by using the ratio edge detection (ROA), and it is marked as a spill. Oil suspected area (AOI), and then apply the improved CFAR detection algorithm to these AOIs for adaptive partition detection, detect the final oil spill area, and extract relevant information. This method can better adapt to the complex and localized situation of the sea surface background in SAR images, and obtain high-precision detection results. Specifically include the following steps:

[0038] Step 1: Precise processing of the whole scene image: including SAR image LEE and MAP Gamma filtering, geometric correction, etc.;

[0039] Step 2: Separation of sea and land, shielding land. Apply Markov random field theory to se