This paper investigates a new regularization of the group-sparsity estimation problem based on a quadratic envelope operator. The resulting estimator is shown to have a reduced bias when compared to the classical LASSO estimator and is characterized by a simple hyperparameter selection. Numerical results show that the quadratic envelope regularization yields estimates equal to an oracle solution with high probability. The robustness of the proposed hyperparameter selection rule is also analyzed.