<p>This work presents an approach for novel modification to technique of improving low-contrast images while maintaining their original brightness. Conventional approaches frequently generate undesirable changes in visual quality because they are unable to strike a balance between keeping brightness and increasing contrast. So, we proposed a modified technique that combines fuzzy logic-based histogram's partition by maxima and minima peak with an entropy-controlled factor modification system to improve contrast while preserving brightness. This method preserves crucial information in both bright and dark regions by remapping pixel intensity while leaving the fuzzy histogram's maximum and minimum peaks intact. Furthermore, we include an entropy-controlled component to the factor value computation method to provide a balanced grey level distribution across low-frequency bins. The image's underlying information content directs the enhancement process using this method of factor adjustment, preventing over-amplification of specific intensity ranges. Simulations on a variety of low-contrast grayscale and color images show the efficiency of the suggested method. Comparative analysis with current approaches reveals increased performance in terms of contrast enhancement and brightness retention. Qualitative evaluations produce visually appealing results with better detail and overall image quality.</p>