基于引力模型的海洋锋信息提取

Application of the Model of Universal Gravity to Oceanic Front Detection Near the Kuroshio Front

海洋锋面是海洋水团特性明显不同的两种或几种水体之间的狭窄过渡带。本文旨在对遥感反演海洋温度场数据(SST),引入引力模型进行海洋锋面的检测。鉴于海洋锋受噪声干扰大,锋面强度小的特点,本文提出了基于引力算法的引力模型。其中,引力算法是将温度数据中的每一个像元点都作为一个独立的天体,其质量对应该像元的温度值,根据引力定律计算3×3区域中,邻域像元对中心点像元的引力和。模型首先对原始数据进行去0处理,为消除对原始数据明暗程度的依赖,对3×3区域数据进行归一化,然后利用函数对归一化后的数据进行增强处理,最后,以引力算法进行锋面检测。验证表明,该模型能有效强化不同区域或水体差异性,并能够有效针对海洋锋信息进行提取,受噪声影响小。

Oceanic front is a narrow transitional zone that the penetration of sea is obviously different between two or more waters there, and it plays an important role in the national production, national defense, marine and weather. Based on the modified theory of universal gravity, sea surface temperature （SST） data near the Kuroshio front are used for front detection. The theory of universal gravity assumes that each image pixel is a celestial body with a mass represented by its value. According to the law of universal gravity, the forces of the pixels in the 3 × 3 neighbourhood exerted on the central pixels can be calculated. Because fronts are susceptible to the noise and intense of fronts are commonly low, a modified method are proposed to solve these problems in this ar- ticle. This method firstly eliminates the pixels that values equal to 0. Then in order to decrease the reliance on the brightness level of original data, a normalization step is applied to each 3 x 3 neighbourhood and next based on image enhancement function, each normalized 3 × 3 area can be enhanced. Finally, the theory of universal gravity is applied to enhanced data for front detection. The algorithm was tested and compared with conventional methods using in the fronts detection such as Sobel, Jensen-Sharmon. The results show that compared to conventional methods in some areas, the proposed algorithm can decrease noise while not cause fronts discontinuous.