import numpy as np

class BayesPreprocessor:

    @staticmethod

    def bayes_noise_removal(image, o):

        # implement image processing

        S1 = image

        S2 = 255 - S1

        S3 = S1 + S2

        try:

            w = S2 / S3

        except ZeroDivisionError:

            w = 0

        w = np.divide(S2, S3)

        p = np.divide(S3, w)

        try:

            p = S3 / w

        except ZeroDivisionError:

            p = 0

        dv = np.log(np.i0((p * np.sinc(w) * S1) / o ** 2)) + np.log(np.i0((p * np.sinc(1 - w) * S2) / o ** 2)) - p * (

                ((np.sinc(w)) ** 2 + (np.sinc(1 - w)) ** 2) / (2 * o ** 2))

        dv[dv < 0] = 0

        return dv