An illumination and affine invariant descriptor is proposed for registering aerial images with large illumination changes and affine transformation, low overlapping areas, monotonous backgrounds or similar features. Firstly, triangle region is detected by K-nearest neighbors (K-NN) graph of initial matched result by Scale-Invariant Feature Transform (SIFT). In order to improve the accuracy, region growth is applied to boost small and slender triangles. Then illumination and affine invariant descriptor is defined to describe triangle regions and measure their similarity. The descriptor named as IIMSA is the combination of MultiScale Autoconvolution (MSA) and multiscale retinex (MSR). The performance of the descriptor is evaluated with optical aerial images and the experimental results demonstrate that the proposed descriptor IIMSA is more distinctive than MSA and SIFT.
Edge detection technology of oil spills image on the sea is one of most key technologies to monitor oil spills on the
sea. This paper presents a new method to detect continuous and closed edges of oil slick infrared (IR) aerial images on
the sea. The method is composed of two stages: determination of edge points and edge linking. Non-maximal
suppression and self-adaptive dynamic block threshold (SADBT) algorithm are applied to determine edge points. Then
an improved edge linking algorithm is used for linking discrete edge points into closed edge contours, according to a cost
function of the combination of Euclidean distance, intensity and angle information of edge ending points to improve the
edge linking decision. Using the proposed algorithm, we can gain continuous and closed edges of oil slick IR aerial
images, thereby confirming the location and acreage of oil spill. The experiment results have shown that the proposed
method improves the degree of automation of edge detection, suppresses the striping noise, intensity inhomogeneity and
weak edge boundaries effectively.
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