Quantum Noise Removal from Breast Mammograms Using Genetic Programming based Hybrid Ensemble Filter

Quantum noise are more likely to occur in mammographic images and it effects the accuracy of classification. In this paper, Genetic Programming (GP) based novel hybrid ensemble method designed for noise amputation from breast mammogram images has been proposed. Three different filters Frost filter, Weiner filter and Non Local Means has been fused by using Genetic Programming for noise removal. The fused GP based filter calculate the value by combining three filters and replacing them with the noisy pixels. Peak signal to noise ratio (PSNR) and Structure Similarity Index measure (SSIM) as a quantitative measures has been employed for evaluation of proposed method with different existing methods. Experimental results show that proposed method bring forward better results as compared to existing methods.