  Lucky imaging is a high-resolution astronomical image recovery technique with
two classic implementation algorithms, i.e. image selecting, shifting and
adding in image space and data selecting and image synthesizing in Fourier
space. This paper proposes a novel lucky imaging algorithm where with
space-domain and frequency-domain selection rates as a link, the two classic
algorithms are combined successfully, making each algorithm a proper subset of
the novel hybrid algorithm. Experimental results show that with the same
experiment dataset and platform, the high-resolution image obtained by the
proposed algorithm is superior to that obtained by the two classic algorithms.
This paper also proposes a new lucky image selection and storage scheme, which
can greatly save computer memory and enable lucky imaging algorithm to be
implemented in a common desktop or laptop with small memory and to process
astronomical images with more frames and larger size. Besides, through
simulation analysis, this paper discusses the binary star detection limits of
the novel lucky imaging algorithm and traditional ones under different
atmospheric conditions.
