dct.py 文件源码

def zz(matrix, nb):
    r"""Zig-zag traversal of the input matrix
    :param matrix: input matrix
    :param nb: number of coefficients to keep
    :return: an array of nb coefficients
    """
    flipped = np.fliplr(matrix)
    rows, cols = flipped.shape  # nb of columns

    coefficient_list = []

    for loop, i in enumerate(range(cols - 1, -rows, -1)):
        anti_diagonal = np.diagonal(flipped, i)

        # reversing even diagonals prioritizes the X resolution
        # reversing odd diagonals prioritizes the Y resolution
        # for square matrices, the information content is the same only when nb covers half of the matrix
        #  e.g. [ nb = n*(n+1)/2 ]
        if loop % 2 == 0:
            anti_diagonal = anti_diagonal[::-1]  # reverse anti_diagonal

        coefficient_list.extend([x for x in anti_diagonal])

    # flattened = [val for sublist in coefficient_list for val in sublist]
    return coefficient_list[:nb]