Apparatus and method for calculating motion vector

1. An apparatus for obtaining a motion vector comprising:

at least one processor configured to receive a long exposure image of a current frame and a short exposure image of the current frame, and obtain a motion vector of the long exposure image of the current frame and a motion vector of the short exposure image of the current frame,

wherein the processor is configured to extract feature points in the long exposure image of the current frame based on a saturation degree of the long exposure image of the current frame, and obtain the motion vector of the long exposure image of the current frame based on a difference between the long exposure image of the current frame and a long exposure image of a previous frame,

wherein the processor is configured to extract feature points in the short exposure image of the current frame, and obtain the motion vector of the short exposure image of the current frame based on a difference between a short exposure image of the current frame and a short exposure image of a previous frame based on a saturation degree of the short exposure image of the current frame, and

wherein, in the extracting the feature points in the long exposure image of the current frame, based on a number of saturated pixels in the long exposure image of the current frame being greater than or equal to a threshold value, the processor is configured to increase a number of sub-regions included in a region of the long exposure image of the current frame, and extract feature points among the feature points of the sub-regions included in the long exposure image of the current frame.

2. The apparatus of claim 1 , wherein the processor is configured to extract the feature points among the feature points of the sub-regions included in the long exposure image of the current frame, by a predetermined number in an order of saturation degree of each of the sub-regions.

3. The apparatus of claim 1 , wherein the processor is configured to extract the feature points among the feature points of the sub-regions included in the long exposure image of the current frame, by a predetermined number in an order of increasing edge strength.

4. The apparatus of claim 3 , wherein the edge strength corresponds to a contrast level between adjacent pixels included in each of the sub-regions.

5. The apparatus of claim 1 , wherein, in the obtaining the motion vector of the long exposure image of the current frame, the processor is configured to obtain local motion vectors in sub-regions corresponding to respective feature points in the long exposure image of the current frame, and obtain a global motion vector of the long exposure image of the current frame based on the local motion vectors.

6. The apparatus of claim 1 , wherein the processor is configured to obtain local motion vectors based on an average of a sum of absolute values of differences of pixels in blocks included in images having a same exposure level.

7. The apparatus of claim 1 , wherein, in the obtaining the motion vector of the short exposure image of the current frame, the processor is configured to obtain local motion vectors in corresponding sub-regions of respective feature points in the long exposure image of the current frame, and

based on a number of saturated pixels included in the short exposure image of the current frame being greater than or equal to a threshold value, the processor is configured to divide a plurality of sub-regions into sub-region sets and obtain a global motion vector based on an average of the local motion vectors of the feature points included in each of the sub-region sets.

8. The apparatus of claim 7 , wherein the processor is configured to obtain the average of the local motion vectors of the feature points included in each of the sub-region sets, for one or more sub-region set among the sub-region sets in which a number of low-saturated pixels is equal to or greater than a threshold value.

9. The apparatus of claim 1 , wherein, in the obtaining the motion vector of the short exposure image of the current frame, the processor is further configured to preprocess the short exposure image of the current frame by performing gamma correction prior to extracting the feature points of the short exposure image of the current frame.

10. The apparatus of claim 1 , wherein the processor is further configured to perform motion compensation for the long exposure image of the current frame based on the motion vector of the long exposure image of the current frame, and perform motion compensation for the short exposure image of the current frame based on the motion vector of the short exposure image of the current frame.

11. A method of obtaining a motion vector based on a motion vector calculation apparatus comprising at least one processor, the method comprising:

receiving a long exposure image of a current frame and a short exposure image of the current frame;

extracting feature points included in the long exposure image of the current frame based on a saturation degree of the long exposure image of the current frame and obtaining a motion vector of the long exposure image of the current frame based on a difference between a long exposure image of the current frame and a long exposure image of a previous frame; and

extracting feature points included in the short exposure image of the current frame and obtaining a motion vector of the short exposure image of the current frame based on a difference between a short exposure image of the current frame and a short exposure image of a previous frame based on a saturation degree of the short exposure image of the current frame,

wherein the obtaining the motion vector of the long exposure image of the current frame comprises:

increasing a number of sub-regions included in a region of the long exposure image of the current frame based on a number of saturated pixels in the long exposure image of the current frame being equal to or greater than a threshold value; and

extracting feature points among the feature points of the sub-regions included the long exposure image of the current frame.

12. The method of claim 11 , wherein the

extracting feature points among the feature points of the sub-regions included the long exposure image of the current frame is performed, by a predetermined number in an order of saturation degree of each of the sub-regions.

13. The method of claim 11 , wherein the

extracting feature points among the feature points of the sub-regions included in the long exposure image of the current frame is performed, by a predetermined number in an order of increasing edge strength.

14. The method of claim 13 , wherein the edge strength corresponds to a contrast level between adjacent pixels included in each of the sub-regions.

15. The method of claim 11 , wherein the obtaining the motion vector of the long exposure image of the current frame comprises:

obtaining local motion vectors in sub-regions corresponding to respective feature points in the long exposure image of the current frame; and

obtaining a global motion vector of the long exposure image of the current frame based on the local motion vectors.

16. The method of claim 11 , wherein the obtaining the motion vector of the long exposure image of the current frame comprises:

obtaining local motion vectors based on an average of a sum of absolute values of differences of pixels in blocks included in the long exposure image.

17. The method of claim 11 , the obtaining the motion vector of the short exposure image of the current frame comprises:

obtaining local motion vectors in sub-regions corresponding to respective feature points in the long exposure image of the current frame, and

dividing a plurality of sub-regions into sub-region sets and obtaining a global motion vector of the short exposure image of the current frame based on an average of the local motion vectors of the feature points included in each of the sub-region sets, based on a number of saturated pixels included in the short exposure image being equal to or greater than a threshold value.

18. The method of claim 17 , wherein, in obtaining the global motion vector of the short exposure image of the current frame, the average of the local motion vectors of the feature points included in each of the sub-region sets among the sub-region sets is obtained for only a sub-region set in which the number of low-saturated pixels is equal to or greater than a threshold value.

19. The method of claim 11 , wherein the obtaining the motion vector of the short exposure image of the current frame comprises:

preprocessing the short exposure image of the current frame by performing gamma correction prior to extracting the feature points.

20. The method of claim 11 , further comprising:

performing motion compensation for the long exposure image of the current frame based on the motion vector of the long exposure image of the current frame; and

performing motion compensation for the short exposure image of the current frame based on the motion vector of the short exposure image of the current frame.