Data compression method based on sampling and estimation

1. A data compression method based on sampling and estimation, comprising:

receiving a piece of data, wherein the piece of data comprises M data regions;

extracting N data regions from the M data regions of the piece of data, wherein N<M, and N and M are both positive integers;

examining a data redundancy ratio in the N data regions; and

determining, according to a value of the data redundancy ratio, whether to compress the piece of data.

2. The data compression method based on sampling and estimation according to claim 1 , wherein the determining, according to a value of the data redundancy ratio, whether to compress the piece of data is determining whether a ratio of the number of completely data-redundant areas to the number of the extracted data regions is equal to or more than a threshold.

3. The data compression method based on sampling and estimation according to claim 2 , further comprising: determining the number of extracted data regions of a next piece of data based on the data redundancy ratio of the current piece of data.

4. A data compression method based on sampling and estimation, comprising:

performing the following steps in sequence on each of a plurality of pieces of data, wherein an i th piece of data comprises M i data regions:

extracting N 1 data regions from the M i data regions of the i th piece of data, wherein N<M, and N, M, and i are all positive integers;

examining data redundancies in the N i data regions;

when a ratio of the number of completely data-redundant areas to the number of the extracted data regions is equal to or more than a threshold, storing the i th piece of data in a buffer; and

when a compression condition is satisfied, compressing an x th piece of data to the i th piece of data in the buffer, wherein the compression condition is

∑

x

i

⁢

N

i

M

i

≤

⁢

K

⁢

⁢

and

⁢

⁢

∑

x

i

+

1

⁢

N

i

M

i

>

K

,

 and x and K are positive integers.

5. The data compression method based on sampling and estimation according to claim 4 , wherein the compression condition further comprises that a data redundancy ratio of the i th piece of data is less than the threshold, and if the data redundancy ratio of the i th piece of data is less than the threshold, the i th piece of data is not compressed, and the data in the buffer is compressed.

6. The data compression method based on sampling and estimation according to claim 4 , wherein K is 1.

7. The data compression method based on sampling and estimation according to claim 4 , wherein

N

i

M

i

of each piece of the data is the same.

8. The data compression method based on sampling and estimation according to claim 4 , wherein

N

i

M

i

of each piece of the data is not completely the same.

9. The data compression method based on sampling and estimation according to claim 4 , further comprising: determining the number of extracted data regions of a next piece of data based on the data redundancy ratio of the current piece of data.

10. The data compression method based on sampling and estimation according to claim 4 , wherein the threshold is in a range of 50% to 100%.