在Block Mean Value Based Image Perceptual Hashing 中，Bian Yang 提出了一种散列方法，它说：
第一个感知散列函数基于均值
a) Normalize the original image into a preset sizes;
b) Divide the size-normalized image I into non overlapped blocks I1, I2, …, IN,
in which N is the block number equal to length of the final hash bit string;
c) Calculate the mean value sequence {M1, M2, …, MN} from corresponding
block sequence {I’1, I’2, …, I’N } and obtain the median value Md of
this sequence as: Md = median (Mi) (i=1,2,…, N)
d) Normalize the mean value sequence into a binaryform and obtain the hash
values h as:
h(i)=0 if Mi<Md
h(i)=1 if Mi>= Md
我的问题在“b”部分，有人知道图像是如何分成块的吗？是这样的吗？
