Denoising algorithms to infrared star map of daytime star observation

Single-point noise(SPN) and stripe non-uniformity (SNU) noise are two typical noises in infrared star map of daytime star observation, which seriously affect subsequent processing of star recognition. Considering the causes and characteristics of the two noises, an improved SPN denoising algorithm was proposed to denoise SPN. The full map was scanned by a local window to detect SPN, and the SPN was instead by global mean value. And a colum histogram offset correction (CHOC) algorithm was proposed to denoise SNU noise. According to the colum offset correction model, the offset of histogram peak position between colum histogram and global histogram was corrected. Experimental results indicate that the algorithms proposed could achieve good denoising effects with infrared star map, and the peak signal-to-noise ratio of star point target could be raised from 7.4 to 12.8, meanwhile, the algorithms could finish in one frame time with low computation complexity, so the algorithms meet the requirements of real-time star map preprocessing application.