Diagnosis of breast cancer dramatically reduces the mortality rate in the female population. mamography image processing is a computer aided method which enhances the amount of detail visible on a digitalized image. The effect of this technique in the diagnoses of breast cancer, where the detection of early malignant tumors is essential for effective treatment, is reviewed in this paper. The mammograms display a small percentage of the information they detect and that is due to the minor difference between normal glandular tissues and malignant disease. The digital medical image processing uses denoising and image enhancement techniques so as to reveal any tumors that may not be obvious and help the surgeons decide. The idea is to transform the data into the wavelet basis, in which the large coefficients are mainly the signal and the smaller ones represent the noise and using particle swarm optimization for high precision and feature detection. In this paper we employ evolutionary method of image enhancement, Particle swarm optimization algorithm and wavelet decomposition accompany with denoising are implemented and the conclusion would be satisfied