To push the 100-plex envelope of suspension array technology, we have developed fully automated methods to acquire multispectral images of multiplexed quantum-dot (QD) encoded microspheres, to segment them in the images, to classify them based on their color code, and to quantify the multiplexed assays. Instead of coding microspheres with two colors and n levels, microspheres were coded with n colors and two levels (present or absent), thus transforming the classification problem from analog to digital. Images of multiplexed microspheres, sedimented at the bottom of microwells, were acquired through a tunable filter at the peak luminescence wavelength of each QD coding species in the system and the assay label wavelength. Another image of the light scattered from microspheres was captured in the excitation bandwidth that was utilized to localize microspheres in multispectral luminescence images. Objects in the acquired images are segmented and luminescence from each identified microsphere in each channel is recorded, based on which the "color code" of each microsphere is determined by applying a mathematical model and a classification algorithm. Our image analysis procedures could identify and classify microspheres with more than 97% accuracy, and the assay CVs were under 20%. These proof-of-principle results demonstrate that highly multiplexed quantification of specific proteins is possible with this rapid, small-sample volume format.