1. A method for detecting a banding region in an image, the method comprising:
segmenting at least one first image into at least one homogeneous color region;
estimating the linear transition of color intensity for the at least one homogeneous color region; and
if the linear transition of color intensity is substantially smooth, classifying the at least one homogenous color region as a banding region;
determining a surface fitting error between the estimated intensity surface and the actual intensity surface in the at least one first image; and
wherein if the surface fitting error is less than a predetermined threshold, determining the linear transition of color intensity is substantially smooth.
2. The method of claim 1, wherein the estimating step includes modeling the intensity surface of pixels in the segmented region using a linear surface model.
3. The method of claim 2, wherein the classifying step includes fitting the estimated intensity surface to the actual intensity surface in the at least one first image.
4. The method of claim 1, wherein the segmenting step includes performing a mean shift function to the at least one first image.
5. The method of claim 1, further comprising:
determining a number of pixels of the at least one segmented region; and
if the number of pixels is less than a predetermined threshold, discarding the at least one segmented region.
6. The method of claim 1, further comprising:
calculating a variance of the color distribution of pixels of the at least one segmented region; and
if the calculated variance is greater than a predetermined threshold, discarding the at least one segmented region.
7. The method of claim 1, further comprising:
determining if each of the at least one classified banding regions share a common border; and
if at least two classified banding regions share a common border, merging the at least two classified banding regions into a single banding region.
8. The method of claim 1, further comprising:
tracking the detected banding region to at least one second image; and applying an error diffusion function to the detected banding region to mask banding artifacts in the at least one first and second images.
9. The method of claim 8, wherein the applying step further comprises:
selecting a block size of pixels of the at least one image;
determining if at least one block is within the detected banding region; adding a masking signal to the at least one block;
determining a quantization error for the at least one block in the at least one image; and
distributing the quantization error to neighboring blocks.
10. The method of claim 8, wherein the tracking step further comprises:
generating a binary mask for the detected banding region of the at least one first image; and
projecting the binary mask to the at least one second image to track the detected banding region.
11. An apparatus for detecting a banding region in an image, the apparatus comprising:
an image segmentation module configured for segmenting at least one first image into at least one homogeneous color region;
a linear transition estimator configured for estimating the linear transition of color intensity for the at least one homogeneous color region; and
a region detection module configured for classifying the at least one homogenous color region as a banding region if the linear transition of color intensity is substantially smooth,
wherein the region detection module is further configured for determining a surface fitting error between the estimated intensity surface and the actual intensity surface in the at least one first image;
and wherein if the surface fitting error is less than a predetermined threshold, determining the linear transition of color intensity is substantially smooth.
12. The apparatus of claim 11, wherein the linear transition estimator is further configured for modeling the intensity surface of pixels in the segmented region using a linear surface model.
13. The apparatus of claim 12, wherein the region detection module is further configured for fitting the estimated intensity surface to the actual intensity surface in the at least one first image.
14. The apparatus of claim 11, wherein the image segmentation module is further configured for performing a mean shift function to the at least one first image.
15. The apparatus of claim 11, wherein the region detection module is further configured for determining a number of pixels of the at least one segmented region; and
if the number of pixels is less than a predetermined threshold, discarding the at least one segmented region.
16. The apparatus of claim 11, wherein the region detection module is further configured for calculating a variance of the color distribution of pixels of the at least one segmented region; and if the calculated variance is greater than a predetermined threshold, discarding the at least one segmented region.
17. The apparatus of claim 11, wherein the region detection module is further configured for determining if each of the at least one classified banding regions share a common border; and if at least two classified banding regions share a common border, merging the at least two classified banding regions into a single banding region.
18. The apparatus of claim 11, further comprising:
a tracking module configured for tracking the detected banding region in the at least one first image to at least one second image; and
an error diffusion module configured for applying an error diffusion function to the detected banding region to mask banding artifacts in the at least one first and second images.
19. The apparatus of claim 18, wherein the error diffusion module further comprises a signal generator configured for generating a masking signal to be applied to at least one image;
wherein the error diffusion module is further configured for selecting a block size of pixels of the at least one image, determining if at least one block is within the detected banding region;
determining a quantization error for the at least one block in the at least one image; and
distributing the quantization error to neighboring blocks.
20. An apparatus for detecting a banding region in an image comprising:
means for segmenting at least one first image into at least one homogeneous color region;
means for estimating the linear transition of color intensity for the at least one homogeneous color region; and
if the linear transition of color intensity is substantially smooth, means for classifying the at least one homogenous color region as a banding region,
wherein the means for classifying further comprises means for determining a surface fitting error between the estimated intensity surface and the actual intensity surface in the at least one first image; and
wherein if the surface fitting error is less than a predetermined threshold, means for determining the linear transition of color intensity is substantially smooth.
21. The apparatus of claim 20, wherein the means for estimating further comprises means for modeling the intensity surface of pixels in the segmented region using a linear surface model.
22. The apparatus of claim 21, wherein the means for classifying further comprises means for fitting the estimated intensity surface to the actual intensity surface in the at least one first image.
23. The apparatus of claim 20, wherein the means for segmenting further comprises means for performing a mean shift function to the at least one first image.
24. The apparatus of claim 20, wherein the means for classifying further comprises means for determining a number of pixels of the at least one segmented region; and if the number of pixels is less than a predetermined threshold, means for discarding the at least one segmented region.
25. The apparatus of claim 20, wherein the means for classifying further comprises means for calculating a variance of the color distribution of pixels of the at least one segmented region; and if the calculated variance is greater than a predetermined threshold, means for discarding the at least one segmented region.
26. The apparatus of claim 20, wherein the means for classifying further comprises means for determining if each of the at least one classified banding regions share a common border; and if at least two classified banding regions share a common border, means for merging the at least two classified banding regions into a single banding region.
27. The apparatus of claim 20, further comprising:
means for tracking the detected banding region in the at least one first image to at least one second image; and
means for applying an error diffusion function to the detected banding region to mask banding artifacts in the at least one first and second images.
28. The apparatus of claim 27, wherein the means for classifying further comprises means for generating a masking signal to be applied to at least one image;
means for selecting a block size of pixels of the at least one image, means for determining if at least one block is within the detected banding region;
means for determining a quantization error for the at least one block in the at least one image; and
means for distributing the quantization error to neighboring blocks.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A computer-implemented apparatus for creating reports of noteworthy securities class action lawsuits customized to show potential monetary claims resulting from the lawsuits for securities purchased or acquired by one or more financial entities, the apparatus comprising:
(a) a database of securities class action lawsuits, the lawsuit database including a subset of securities class action lawsuits that are deemed to be noteworthy by the entity that administers the system, and for each financial entity;
(b) a comparator in a computer that compares transaction activity of a financial entity with records in the database subset of securities class action lawsuits to identify any securities purchased or acquired by the financial entity that are associated with a securities class action lawsuit in the lawsuit database and which may provide a potential monetary claim for the financial entity; and
(c) a report creator that automatically creates a report of the noteworthy lawsuits, and for the lawsuits that were identified by the comparator and which are deemed to be noteworthy, the report including the potential monetary claim for the financial entity based on the transaction activity of the financial entity.
2. The apparatus of claim 1 wherein the lawsuits that are deemed noteworthy are lawsuits where the potential market loss for all eligible parties is greater than a predetermined value.
3. A computer-implemented apparatus for creating watchlist reports of securities class action lawsuits of interest to financial entities customized to show potential monetary claims resulting from the lawsuits for securities purchased or acquired by one or more financial entities, the apparatus comprising:
(a) a database of securities class action lawsuits;
(b) a watchlist database of lawsuits maintained for each financial entity which includes a subset of lawsuits in the lawsuit database that are identified by the financial entity as lawsuits of particular interest;
(c) a comparator in a computer that compares transaction activity of a financial entity with records in the database subset of securities class action lawsuits to identify any securities
purchased or acquired by the financial entity that are associated with a securities class action lawsuit in the lawsuit database and which may provide a potential monetary claim for the financial entity; and
(d) a watchlist report creator that automatically creates a watchlist report of the watchlist lawsuits, and for the lawsuits that were identified by the comparator and which are on the watchlist, the watchlist report including the potential monetary claim for the financial entity based on the transaction activity of the financial entity.
4. The apparatus of claim 3 wherein the watchlist report further includes an action recommended to be taken by the financial entity for the lawsuits that were identified by the comparator.
5. The apparatus of claim 3 wherein the watchlist report further includes the case status for each of the lawsuits.