Breast cancer is a fatal disease which occurs in men and women both but majority of cases belong to women. Since the mortality rate of this disease is very high, accurate diagnostic methods are needed for early identification of this disease. Among all diagnostic methods, histopathology approach is a gold standard. By analyzing microscopic images, pathologist can accurately evaluate if the breast cancer is benign or malignant. Microscopic images generally suffer from noise and poor contrast which may hinder the accurate diagnosis. Hence for accurate diagnosis, denoising and enhancement of microscopic images are necessary for overcoming the issue of noise and low contrast, while preserving crucial characteristics of microscopic images. In this paper, various denoising and enhancement techniques such as median filter, wiener filter, bilateral filter, non-local means filter, anisotropic diffusion, fourth order partial differential equation filter, contrast limited adaptive histogram equalization, histogram equalization and unsharp masking are discussed. A quantitative and qualitative comparison has been carried out for all the techniques. By analyzing quantitative and visual results obtained, it is observed that the fourth order partial differential equation filter along with unsharp masking showed better results.