Automated statistical self-calibrating detection and removal of blemishes in digital images based on determining probabilities based on image analysis of single images

1. A digital image acquisition device, comprising a lens assembly, a sensor array, a processor and a memory having code stored therein for programming the processor to perform a method of automatically correcting dust artifact within images acquired by the device, wherein the method comprises:

(a) determining probability of dust artifact regions corresponding to pixels within a digitally-acquired image based at least in part on a pixel analysis of the region in view of predetermined characteristics indicative of the presence of a dust artifact region;

(b) associating the dust artifact regions with one or more extracted parameters relating to the optical system when the image was acquired;

(c) forming a statistical dust map including mapped dust regions based on the dust artifact determining and associating; and

(d) correcting digital data corresponding to correlated dust artifact regions within said digitally-acquired image or a different image, or both, based on the associated statistical dust map, and

(e) wherein the dust artifact determining includes:

(I) loading the statistical dust map;

(II) loading extracted parameter information of a present image;

(III) performing a calculation for relating the statistical dust map with at least one of the images according to a selected value of at least one extracted parameter; and

(IV) comparing dust artifact detection data with the statistical dust map data.

2. The device of claim 1 , wherein the method further comprises eliminating certain suspected dust artifact regions as having a probability below a first threshold value.

3. The device of claim 1 , wherein the method further comprises judging certain probable dust artifact regions as having a probability above a threshold value such as to be subject to said correcting operation.

4. The device of claim 1 , wherein said probability determining includes weighting suspected dust artifact regions according to one or more predetermined probability weighting assessment conditions.

5. The device of claim 1 , wherein the method further comprises correcting pixels corresponding to correlated dust artifact regions within said original images based on the associated statistical dust map.

6. The device of claim 1 , wherein the method further comprises digitally-acquiring additional images with said digital camera, repeating said determining and associating, and updating said statistical dust map including updating said mapped dust regions based on the additional dust artifact determining and associating.

7. The device of claim 1 , wherein said determining includes dynamically updating said probabilities based on comparisons with suspected equivalent dust artifact regions within said further digitally-acquired images.

8. The device of claim 1 , wherein said forming includes dynamically updating said statistical dust map based on further pixel analyses of suspected dust artifact regions in further images in view of predetermined characteristics indicative of the presence of a dust artifact region.

9. The device of claim 1 , wherein the method further comprises validating whether said further digitally-acquired image has non contradicting data that said probability that certain pixels correspond to dust artifact regions within said further digitally-acquired image priori to correcting pixels corresponding to correlated dust artifact regions within further digitally-acquired images based on the associated statistical dust map.

10. The device of claim 1 , wherein for the performing, the at least one extracted parameter is otherwise uncorrelated between the present image and the dust map.

11. One or more processor-readable devices having code stored therein for programming a processor to perform a method of automatically correcting dust artifact within images acquired by the device, wherein the method comprises:

(a) determining probability of dust artifact regions corresponding to pixels within a digitally-acquired image based at least in part on a pixel analysis of the region in view of predetermined characteristics indicative of the presence of a dust artifact region;

(b) associating the dust artifact regions with one or more extracted parameters relating to the optical system when the image was acquired;

(c) forming a statistical dust map including mapped dust regions based on the dust artifact determining and associating; and

(d) correcting digital data corresponding to correlated dust artifact regions within said digitally-acquired image or a different image, or both, based on the associated statistical dust map, and

(e) wherein the dust artifact determining includes:

(I) loading the statistical dust map;

(II) loading extracted parameter information of a present image;

(III) performing a calculation for relating the statistical dust map with at least one of the images according to a selected value of at least one extracted parameter; and

(IV) comparing dust artifact detection data with the statistical dust map data.

12. The one or more processor-readable devices of claim 11 , wherein the method further comprises eliminating certain suspected dust artifact regions as having a probability below a first threshold value.

13. The one or more processor-readable devices of claim 11 , wherein the method further comprises judging certain probable dust artifact regions as having a probability above a threshold value such as to be subject to said correcting operation.

14. The one or more processor-readable devices of claim 11 , wherein said probability determining includes weighting suspected dust artifact regions according to one or more predetermined probability weighting assessment conditions.

15. The one or more processor-readable devices of claim 11 , wherein the method further comprises correcting pixels corresponding to correlated dust artifact regions within said original images based on the associated statistical dust map.

16. The one or more processor-readable devices of claim 11 , wherein the method further comprises digitally-acquiring additional images with said digital camera, repeating said determining and associating, and updating said statistical dust map including updating said mapped dust regions based on the additional dust artifact determining and associating.

17. The one or more processor-readable devices of claim 11 , wherein said determining includes dynamically updating said probabilities based on comparisons with suspected equivalent dust artifact regions within said further digitally-acquired images.

18. The one or more processor-readable devices of claim 11 , wherein said forming includes dynamically updating said statistical dust map based on further pixel analyses of suspected dust artifact regions in further images in view of predetermined characteristics indicative of the presence of a dust artifact region.

19. The one or more processor-readable devices of claim 11 , wherein the method further comprises validating whether said further digitally-acquired image has non contradicting data that said probability that certain pixels correspond to dust artifact regions within said further digitally-acquired image priori to correcting pixels corresponding to correlated dust artifact regions within further digitally-acquired images based on the associated statistical dust map.

20. The one or more processor-readable devices of claim 11 , wherein for the performing, the at least one extracted parameter is otherwise uncorrelated between the present image and the dust map.