Anomaly Detection System

Abstract

An image analysis system including an image gathering unit that gathers a high-altitude image having multiple channels, an image analysis unit that segments the high-altitude image into a plurality of equally size tiles and determines an index value based on at least one channel of the image where the image analysis unit identifies areas containing anomalies in each image.

What is claimed: 
     
         1 . An image analysis system including:
 an image capture unit that captures at least one a high-altitude image having multiple channels;   an image analysis unit operating in the memory of a computer that segments the high-altitude image into a plurality of tiles with each tile having a same pixel width and a same pixel height as an adjacent tile and determines an index value based on at least one channel of the image,   wherein   the image analysis unit performs a pixel by pixel analysis of the pixels in each tile to calculate a mean value for each tile,   the image analysis unit applies a Gaussian distribution of the image pixel values to identify outlying values, and   the image analysis unit normalizes the image after applying the Gaussian distribution and calculates a mean and standard deviation values of each pixel, and   the image analysis unit identifies areas containing anomalies in each image by analyzing the mean value for each area connected to identified anomalies to determine areas where anomalies exist, and   a score is assigned to each identified anomaly and an anomaly rectangle is placed on the image to identify areas where anomalies are identified.   
     
     
         2 . The image analysis system of  claim 1 , wherein the index determined is a normal differential vegetation index for a segment of the captured image. 
     
     
         3 . The image analysis system of  claim 1 , wherein the index determined is a soil adjusted vegetation index for a segment of the captured image. 
     
     
         4 . The image analysis system of  claim 1 , wherein the image analysis unit masks the segment of the image using a confidence mask based on the index value. 
     
     
         5 . The image analysis system of  claim 1 , wherein the image analysis unit applies a box averaging threshold to the segment of the normalized image. 
     
     
         6 . The image analysis system of  claim 5 , wherein the image analysis unit calculates a mean for each pixel in the applied box. 
     
     
         7 . The image analysis system of  claim 6 , wherein the image analysis unit removes pixels from the segment of the image that have a calculated mean below a predetermined threshold. 
     
     
         8 . The image analysis system of  claim 7 , wherein the image analysis unit calculates a score for each of the remaining pixels and draws a rectangle around groups of pixels based on the scores of each pixel. 
     
     
         9 . An image analysis unit including a processor and a memory with a method of analyzing an image performed in the memory, the method including the steps of:
 gathering a high-altitude image having multiple channels via an image capture unit;   segmenting the high-altitude image into a plurality of tiles with each tile having a same pixel width and a same pixel height as an adjacent tile via an image analysis unit;   determining an index value based on at least one channel of the image via the image analysis unit;   applying a Gaussian distribution of the image pixel values to identify outlying values, and   normalizing the image after applying the Gaussian distribution and calculates a mean and standard deviation values of each pixel,   identifying areas containing anomalies in each image via the image analysis unit by analyzing the mean value for each area connected to identified anomalies to determine areas where anomalies exist, and   assigning a score to each identified anomaly and placing an anomaly rectangle on the image to identify areas where anomalies are identified.   
     
     
         10 . The method of  claim 9 , wherein the index determined is a normal differential vegetation index for a segment of the captured image. 
     
     
         11 . The method of  claim 9 , wherein the index determined is a soil adjusted vegetation index for a segment of the captured image. 
     
     
         12 . The method of  claim 9 , wherein the step of identifying anomalies includes masking the segment of the image using a confidence mask based on the index value. 
     
     
         13 . The method of  claim 12 , wherein the step of identifying anomalies includes applying a box averaging threshold to the segment of the normalized image. 
     
     
         14 . The method of  claim 13 , wherein the step of identifying anomalies includes calculating a mean for each pixel in the applied box. 
     
     
         15 . The method of  claim 14 , wherein the step of identifying anomalies includes removing pixels from the segment of the image that have a calculated mean below a predetermined threshold. 
     
     
         16 . The method of  claim 15 , wherein the step of identifying anomalies includes calculating a score for each of the remaining pixels and drawing a rectangle around groups of pixels based on the scores of each pixel.