A single sensor camera can capture scenes by means of a color filter array. Each pixel samples only one of the three primary colors. We use a color demosaicking (CDM) technique to produce full color images and propose a robust adaptive sparse representation model for high quality CDM. The data fidelity term is characterized by norm to suppress the heavy-tailed visual artifacts with an adaptively learned dictionary, while the regularization term is encouraged to seek sparsity by forcing sparse coding close to its nonlocal means to reduce coding errors. Based on the classical quadratic penalty function technique in optimization and an operator splitting method in convex analysis, we further present an effective iterative algorithm to solve the variational problem. The efficiency of the proposed method is demonstrated by experimental results with simulated and real camera data.