Introducción: Compressive spectral imaging (CSI) captures spectral information at various spatial locations of a spectral image with few compressed projections. Traditionally, the original scene is recovered by assuming sparsity in some known representation basis. In contrast, the matrix completion techniques (MC) rely on a low-rank structure that avoids using any known representation basis. The coded aperture snapshot spectral imager (CASSI) is a CSI optical architecture that modulates light by using a coded aperture with a pattern that determines the quality of reconstruction. The objective of this paper is to design optimal coded aperture patterns when MC is used to recover a spectral scene from CASSI measurements. Metodología: The patterns are attained by maximizing the distance between the translucent elements, which become more precise measurements given the MC constraints. Resultados: Simulations from different databases show an average improvement of 1 to 9 dBs when the designed patterns are used compared to the conventional random and complementary patterns. Discusión y conclusiones: The proposed approach solves an integer optimization problem with a complexity that is commonly NP-hard but that can be reduced with proper relaxation. Finally, an effective alternative method using coded aperture patterns for …