Denoising of medical images using a reconstruction-average mechanism

A beginning to deal with denoising the signals specifically the images is proposed by reconstructing the conventional mechanism. Various constituents of the overall scope are chosen, from each of which a signal can be rebuilt using a Singularity Function Analysis (SFA) model. The concept thus accomplishes denoising by reconstructing the images using the reality that each is the sum of the same image which is free from noise with an additive noise removing process. The observed consequences on both simulated and monochrome images show that the suggested method permits effective denoising while asserting the quality of signal.