http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Sparse Representation Approach to Inverse Halftoning by Means of K-SVD Dictionary
Masahiro Hirao,Toshiaki Aida 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
We approach to the problem of inverse halftoning within the frameworks of Bayesian inference and compressed sensing, which is one of the most effective signal processing methods through sparse representation. In this paper, we adopt the K-SVD dictionary for the sparse representation of an original image to be inferred, and develop our previous work with the DCT dictionary restricted to a small number of the slowest basis vectors. The K-SVD dictionary is known to have higher efficiency for sparse representation than the DCT one. Therefore, we can expect that it helps us overcome a heavily ill-posed property of the problem. Numerical analysis confirms the effectiveness of our approach with the K-SVD dictionary, and makes clear the difference between the characteristics of the K-SVD dictionary and those of the restricted DCT one.