An improved two-dimensional entropy method for star trail tracing in deep sky

The trace of star trail is an important component of deep sky detection. The stars are low contrast targets, and their self-rotation will make their brightness change in cycle. Above all, the trail trace is vulnerable to the block and disturbance of other stars. Traditional one-dimensional maximum entropy thresholding algorithm is vulnerable to the noise, and the calculation of two-dimensional entropy methods is too large and takes too much time. This paper proposes an improved two-dimensional entropy threshold algorithm. We use recursion iteration method to eliminate the redundancy calculation, and reduce the size of two-dimensional histogram based on the deep sky stars characteristic, such as low contrast, fuzziness and the centralized histogram. We also combine our algorithm with the space trail trace model to forecast the star trace. Experiments results show, when the star are blocked or they turn dark, the method still can well extrapolate the star trace. Our method improves the capability of trailing the ebb and small star, and increases the precision of tracing. It is also robust to the noise, so there is a good application foreground for the method.