Comparative Analysis of Noise Reduction Techniques for Body Fluid Image Enhancement

Cancer remains a leading cause of global morbidity and mortality, with late detection significantly reducing the effectiveness of treatment options. Early diagnosis is crucial for improving survival rates, enhancing therapeutic outcomes, and reducing healthcare costs. Among various diagnostic approaches, the analysis of biomarkers in body fluids has gained prominence due to its minimally invasive nature and cost-effectiveness. However, microscopic images of body fluids often suffer from noise and poor quality, hindering accurate diagnosis. This paper investigates the effectiveness of various image filtering techniques, such as Average, Wiener, and Gaussian filters, to body fluid images degraded by Salt and Pepper and Gaussian noise at four levels. By comparing these methods, we aim to identify the most effective filter for denoising and enhancing cell images, thereby supporting the development of more accurate cancer detection systems.