This paper introduces a novel method called minimum mean brightness error bi-histogram equalization (MMBEBHE) to improve contrast enhancement while preserving image brightness. Traditional histogram equalization (HE) often alters image brightness, which is undesirable in consumer electronics. Bi-histogram equalization (BBHE) attempts to preserve brightness but has limitations in certain cases. MMBEBHE extends BBHE by separating the image histogram based on a threshold level, minimizing the absolute mean brightness error (AMBE). An efficient recursive integer-based computation for AMBE is developed to enable real-time implementation. Simulation results on images with varying brightness levels show that MMBEBHE effectively enhances images that HE, BBHE, and dualistic sub-image histogram equalization (DSIHE) struggle with. Additionally, MMBEBHE performs comparably to BBHE and DSIHE on specific sample images from previous studies. The method ensures better brightness preservation while achieving improved contrast enhancement. Keywords: Bi-histogram equalization; Dualistic sub-image; Histogram equalization; Minimum mean brightness error.This paper introduces a novel method called minimum mean brightness error bi-histogram equalization (MMBEBHE) to improve contrast enhancement while preserving image brightness. Traditional histogram equalization (HE) often alters image brightness, which is undesirable in consumer electronics. Bi-histogram equalization (BBHE) attempts to preserve brightness but has limitations in certain cases. MMBEBHE extends BBHE by separating the image histogram based on a threshold level, minimizing the absolute mean brightness error (AMBE). An efficient recursive integer-based computation for AMBE is developed to enable real-time implementation. Simulation results on images with varying brightness levels show that MMBEBHE effectively enhances images that HE, BBHE, and dualistic sub-image histogram equalization (DSIHE) struggle with. Additionally, MMBEBHE performs comparably to BBHE and DSIHE on specific sample images from previous studies. The method ensures better brightness preservation while achieving improved contrast enhancement. Keywords: Bi-histogram equalization; Dualistic sub-image; Histogram equalization; Minimum mean brightness error.