Imputation of Multiple Missing Values by Normal Mixture Model under Markov Random Field: Application to Imputation of Pixel Values of Color Image Kim, Seung-Gu;
There very many approaches to impute missing values in the iid. case. However, it is hardly found the imputation techniques in the Markov random field(MRF) case. In this paper, we show that the imputation under MRF is just to impute by fitting the normal mixture model(NMM) under several practical assumptions. Our multivariate normal mixture model based approaches under MRF is applied to impute the missing pixel values of 3-variate (R, G, B) color image, providing a technique to smooth the imputed values.
Multiple missing values;imputation;Markov random field;EM algorithm;color image;