A novel color correction method of camera based on HSV (Hue, Saturation, and Value) model is proposed in this paper, which aims at the problem that spectrum response of camera differs from the CIE criterion, and that the image color of camera is aberrant. Firstly, the color of image is corrected based on HSV model to which image is transformed from RGB model. As a result, the color of image accords with the human vision for the coherence between HSV model and human vision; Secondly, the colors checker with 24 kinds of color under standard light source is used to compute correction coefficient matrix, which improves the spectrum response of camera and the CIE criterion. Furthermore, the colors checker with 24 kinds of color improves the applicability of the color correction coefficient matrix for different image. The experimental results show that the color difference between corrected color and color checker is lower based on proposed method, and the corrected color of image is consistent with the human eyes.
The calculation of star point centroid is a key step of improving star tracker measuring error. A star map photoed by APS detector includes several noises which have a great impact on veracity of calculation of star point centroid. Through analysis of characteristic of star map noise, an algorithm of calculation of star point centroid based on background forecast is presented in this paper. The experiment proves the validity of the algorithm. Comparing with classic algorithm, this algorithm not only improves veracity of calculation of star point centroid, but also does not need calibration data memory. This algorithm is applied successfully in a certain star tracker.