This paper proposes an alternative optimization-based EMD based on the notions of: 1. local mean points that impose mode symmetry via a Tikhonov regularized least-square (RLS) problem, and 2. efficient bootstrap sifting that guarantees asymptotic convergence of the mean envelope to the local mean points, regardless of regularization. Mathematical proof of convergence and a straightforward extension to the 2D-multivariate setting and CIELAB color images are presented. Performance is demonstrated with a univariate signal and two images. Spectral analysis confirms coordinated feature extraction among image components, and separation of spatial spectra among the intrinsic mode functions.MATLAB code:  https://doi.org/10.24433/CO.8628416.v1