Acute Myeloid Leukemia (AML) is a complex hematological malignancy characterized by the abnormal growth and accumulation of immature myeloid cells. Acute Promyelocytic Leukemia (APL) is one of the subtypes of AML. Microscopic analysis of blood cell images plays a critical role in the diagnosis and prognosis of APL. However, color variations in blood cell images resulting from differences in staining protocols, imaging platforms, and acquisition settings can pose challenges in accurate and consistent interpretation. Color normalization can tackle the problem of variation of color and illumination of APL images. This can enhance the image analysis and facilitate more reliable diagnosis for both hematologists and computerized decisions. This paper studies a different color normalization method for APL images to determine the best color normalization method. Quality performances of different color normalization methods are evaluated and compared in terms of structure similarity index matrix (SSIM), mean absolute error (MAE), correlation coefficient (CO), and root mean square error (RMSE). Our experimental analysis suggests that Standardizing Multiple Color Variations Method (SMCV) provides better output images based on the qualitative and quantitative results.