Low-light images frequently experience poor visibility and reduced contrast, which results in a significant degradation of overall image quality. To address this challenge, this paper introduces a new algorithm designed to improve contrast in low-light images through a modified form of histogram equalization. The proposed method involves dividing the image into multiple layers and applying histogram equalization to each of these layers individually. By this process, local brightness levels are balanced effectively while preserving important image details. As a result, the algorithm generates visually increased images with improved clarity, brightness, and contrast. The effectiveness of the method has been demonstrated through experimental results, showing notable improvements over existing techniques. Various image quality metrics, such as the Naturalness Image Quality Evaluator ( NIQE) and the Colorfulness-based Patch Contrast Quality Index (CPCQI), were used to assess performance, confirming significant enhancements in image quality when compared to traditional methods in image evaluations scores