A Characteristic Extraction Algorithm Based on Blocking Star Images

The star images obtained through the CCD camera can visually display the star structure. In order to get the wide starry image, we need to extract the characteristics of star images to achieve the star image stitching. In the star images, star points, whose characteristics are limited, are easily influenced by noise and are also difficult to extract. The number of stars is too large to stitch accurately. Thus, we propose a stitching algorithm based on blocking star images. First, we establish the maximum intensity projection model based on time sequence to locate the star points accurately. Then, according to the relative positions of star points, the block model is introduced to realize the establishment of the characteristics. Finally, the star image stitching is achieved from the perspective of the characteristic similarity. The experiments illustrate that CM (combination measure) reaches 0.87, and the proposed algorithm has better anti-noise performance and robustness.