This paper introduces a novel extension of bi-histogram equalization (BBHE) called minimum mean brightness error bi-histogram equalization (MMBEBHE) to enhance image contrast while preserving the original brightness. BBHE separates the input image's histogram into two parts based on the input mean and equalizes them independently, but it may not handle cases requiring higher brightness preservation. MMBEBHE improves upon this by separating the histogram based on a threshold level to minimize the absolute mean brightness error (AMBE). The paper formulates an efficient recursive integer-based computation for AMBE to facilitate real-time implementation. Simulation results using sample images with varying mean brightness show that MMBEBHE effectively enhances images that are difficult to handle by traditional methods like histogram equalization (HE) and dualistic sub-image histogram equalization (DSIHE). Additionally, MMBEBHE demonstrates comparable performance to BBHE and DSIHE when tested on specific sample images.This paper introduces a novel extension of bi-histogram equalization (BBHE) called minimum mean brightness error bi-histogram equalization (MMBEBHE) to enhance image contrast while preserving the original brightness. BBHE separates the input image's histogram into two parts based on the input mean and equalizes them independently, but it may not handle cases requiring higher brightness preservation. MMBEBHE improves upon this by separating the histogram based on a threshold level to minimize the absolute mean brightness error (AMBE). The paper formulates an efficient recursive integer-based computation for AMBE to facilitate real-time implementation. Simulation results using sample images with varying mean brightness show that MMBEBHE effectively enhances images that are difficult to handle by traditional methods like histogram equalization (HE) and dualistic sub-image histogram equalization (DSIHE). Additionally, MMBEBHE demonstrates comparable performance to BBHE and DSIHE when tested on specific sample images.