Star smear removal for full-frame charge-coupled device images based on Gaussian fitting

Abstract

.Image smear, produced by the shutter-less operation of full-frame charge-coupled device (CCD) sensors, greatly affects the performance of target detection, the centering accuracy, and visual magnitude estimation. We study the operation principle of full-frame CCDs, analyze the cause and properties of smear effect, and propose a smear removal algorithm for star images of full-frame CCDs. The proposed method locates the smears and extracts the rough profiles of the smeared stars by finding the conditional extrema. Then Gaussian fitting is applied to accurately extract the stars, in order to maintain the integrity of star images while minimizing the smear effect. The extraction of smears and stars requires parameters such as the size of the CCD, the integration time and the readout time, as well as the estimation of background noise. We assess the performance of our scheme with real observed data. The experimental results show that the proposed scheme improves the average signal-to-noise ratio of the images by about 22%, presenting better smear removal performance compared with several published methods. The limitation of the proposed algorithm includes the difficulty of distinguishing between two very close stars displaying the gray level of a single peak and overestimation of the background noise may also influence the performance of the algorithm.

Star Centroiding Based on Fast Gaussian Fitting for Star Sensors

“…The fitting methods estimate the star centroid by fitting the intensity of a star spot to the Gaussian function. As the star spot conforms to a 2-dimensional Gaussian function, the Gaussian fitting algorithm (GF) can in theory achieve the highest star centroiding accuracy [ 11 , 12 , 13 ]. However, since solving the Gaussian parameters is a nonlinear optimization problem, which is inevitably a multiple-step iteration process, the algorithm is quite sensitive to the initial parameters and is time consuming in practice.…”