Enhancement techniques are essential for MRI images to enhance their quality for improved brain tumor diagnosis. This review evaluates multiple image enhancement methods including traditional techniques and advanced deep learning models along with hybrid solutions to determine their effectiveness in identifying tumors. We study the advantages and disadvantages of each of the approaches while referring to some state-of-the-art developments like lightweight models, explainable AI and the amalgamation of several imaging modalities like MRI, and PET scan. Even though significant progress has been made important issues such as limited datasets, high computational demands, and the need for interpretable models still exist. This research delivers important findings to both researchers and practitioners and paves the way for future advances in medical imaging that improve brain tumor diagnostic precision and treatment outcomes.