1. An image processing method, comprising:
an input step inputting a color processing target image obtained through a shooting optical system;
a detecting step detecting a high luminance area included in the color processing target image;
a first discriminating step discriminating whether or not the detected high luminance area is an occurrence area of a color flare;
a second discriminating step discriminating whether or not a color correction is performed on the occurrence area by comparing a value of a color component of a pixel included in the occurrence area with a preset threshold;
a restoring step restoring a color distribution of the occurrence area after the color correction to a color distribution of the occurrence area before the color correction;
a flare estimating step estimating an influence of the color flare in the occurrence area based on the color distribution of the restored occurrence area; and
a reducing step reducing the estimated influence of the color flare from the restored occurrence area.
2. The image processing method according to claim 1, wherein the color correction is saturation enhancement.
3. The image processing method according to claim 2, wherein
in the second discriminating step, when at least one color corrected pixel having a first color component which is less than a noise level and a second color component which is equal to or greater than a saturation level exists in the occurrence area, it is regarded that there is a possibility of the color correction being performed on the occurrence area.
4. The image processing method according to claim 3, wherein the restoring step comprises:
an area setting step setting a processing area including the occurrence area on the processing target image;
a smoothing step smoothing an area having a lower value compared to a value of a peripheral area in a focused color component of the processing area; and
a corrected component calculating step calculating a color corrected component in the focused color component based on a difference between the focused color component before and after being smoothed.
5. The image processing method according to claim 1, wherein
the flare estimating step comprises:
an area setting step setting a processing area including the occurrence area on the processing target image;
a reference color setting step setting a reference color component to be a reference among respective color components of the occurrence area;
a correlation calculating step calculating correlation information indicating a correlation between a reference color component and another color component in the processing area; and
a flare color component estimating step estimating a flare color component being a colored distribution of the color flare based on the correlation information of the processing area and the reference color component of the occurrence area.
6. The image processing method according to claim 1, wherein
in the restoring step and the flare estimating step, a size reduced version of the processing target image is used instead of using the processing target image.
7. A non-transitory computer-readable storage medium storing an image processing program to cause a computer to execute:
an input step inputting a color processing target image obtained through a shooting optical system;
a detecting step detecting a high luminance area included in the color processing target image;
a first discriminating step discriminating whether or not the detected high luminance area is an occurrence area of a color flare;
a second discriminating step discriminating whether or not a color correction is performed on the occurrence area by comparing a value of a color component of a pixel included in the occurrence area with a preset threshold;
a restoring step restoring a color distribution of the occurrence area after the color correction to a color distribution of the occurrence area before the color correction;
a flare estimating step estimating an influence of the color flare in the occurrence area based on the color distribution of the restored occurrence area; and
a reducing step reducing the estimated influence of the color flare from the restored occurrence area.
8. An image processing apparatus, comprising:
an input unit inputting a color processing target image obtained through a shooting optical system;
a detecting unit detecting a high luminance area included in the color processing target image;
a first discriminating unit discriminating whether or not the detected high luminance area is an occurrence area of a color flare;
a second discriminating unit discriminating whether or not a color correction is performed on the occurrence area by comparing a value of a color component of a pixel included in the occurrence area with a preset threshold;
a restoring unit restoring a color distribution of the occurrence area after the color correction to a color distribution of the occurrence area before the color correction;
a flare estimating unit estimating an influence of the color flare in the occurrence area based on the color distribution of the restored occurrence area; and
a reducing unit reducing the estimated influence of the color flare from the restored occurrence area.
9. An imaging apparatus, comprising:
an imaging device capturing an object image formed by a shooting optical system; and
the image processing apparatus according to claim 8.
10. The imaging apparatus according to claim 9, further comprising a shooting lens including a diffractive optical element.
11. The imaging apparatus according to claim 9, wherein
a shooting lens including a diffractive optical element can be attached to the imaging apparatus.
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 method comprising using at least one hardware processor for:
receiving a request of a user for media;
retrieving a first metadata set relating to said media;
comparing between (a) a media usage profile of the user, which profile reflects knowledge of the user, and (b) the first metadata set relating to said media, to identify gaps in the knowledge of the user with respect to said media; and
providing to the user information relating to said identified gaps.
2. The method of claim 1, wherein said providing to the user the information relating to the identified gaps comprises:
(a) generating a gap analysis report comprising a set of facts each representing a gap of said identified gaps,
(b) generating gap summaries for said set of facts based on said gap analysis report and said first metadata set, wherein each of said gap summaries is generated for each fact of said set of facts.
3. The method of claim 2, wherein said providing to the user the information relating to the identified gaps further comprises retrieving a second metadata ser relating to said identified gaps and wherein said generating of gap summaries is based on said second metadata set.
4. The method of claim 1, further comprising using said at least one hardware processor for generating said media usage profile of the user.
5. The method of claim 1, further comprising using said at least one hardware processor for updating the media usage profile of the user with an identifier of said media and a metadata set relating to said request for media.
6. The method of claim 1, wherein said providing to the user of information relating to the identified gaps comprises providing to the user said media integrated with said information.
7. The method of claim 1, further comprising using said at least one hardware processor for providing to said user said media.
8. The method of claim 1, wherein said media is selected from the group consisting of: a video, an image, audio, a text or a combination thereof.
9. A system comprising:
at least one server, the at least one server comprising at least one hardware processor configured to:
i) receive a request for media from a user;
ii) provide said request for media to a knowledge gap predictor, to receive information relating to gaps identified in knowledge of said user with respect to said media;
iii) retrieve said media from a media database; and
iv) provide to said user said media and said information.
10. The system of claim 9, wherein said at least one server further comprises said knowledge gap predictor, and wherein said knowledge gap predictor is configured to:
retrieve a media usage profile of said user from a media usage profile database, said media usage profile reflecting said knowledge of said user;
retrieve a first metadata set relating to said media from a media metadata database; and
compare between said media usage profile of said user and said first metadata set relating to said media, to identify said gaps in knowledge of said user with respect to said media.
11. The system of claim 10, wherein said knowledge gap predictor is further configured to:
generate a gap analysis report comprising a set of facts, wherein each fact of said set of facts represents a gap of said gaps identified in said knowledge of said user, and
provide to a media gap summarizer said gap analysis report, to receive said information.
12. The system of claim 11, wherein said at least one server further comprises said media gap summarizer, and wherein said media gap summarizer is configured to generate said information based on said gap analysis report and said first metadata set.
13. The system of claim 11, wherein said generating of said information comprises generating gap summaries, wherein a gap summary of said gap summaries is generated for each fact of said set of facts.
14. The system of claim 9, wherein said at least one hardware processor is further configured to provide said request for media to a media usage monitor, to update said knowledge of said user in the context of said request for media.
15. The system of claim 14, wherein said at least one server further comprises said media usage monitor, wherein said media usage monitor is configured to:
retrieve a metadata set relating to said media from a media metadata database, and
update a media usage profile of said user with an identifier of said media and said metadata set in a media usage profiles database, wherein said media usage profile reflects said knowledge of said user.
16. A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to:
receive a request of a user for media;
retrieve a first metadata set relating to said media;
compare between (a) a media usage profile of the user, which profile reflects knowledge of the user, and (b) the first metadata set relating to said media, to identify gaps in the knowledge of the user with respect to said media; and
provide to the user information relating to said identified gaps.
17. The computer program product of claim 16, wherein said providing to the user the information relating to the identified gaps comprises:
(a) generating a gap analysis report comprising a set of facts, wherein each fact of said set of facts represents a gap of said identified gaps, and
(b) generating gap summaries for said set of facts based on said gap analysis report and said first metadata set, wherein a gap summary of said gap summaries is generated for each fact of said set of facts.
18. The computer program product of claim 16, wherein said program code is further executable by said at least one hardware processor to generate said media usage profile of the user.
19. The computer program product of claim 16, wherein said program code is further executable by said at least one hardware processor to update the media usage profile of the user with an identifier of said media and a metadata set relating to said request for media.
20. The computer program product of claim 16, wherein said program code is further executable by said at least one hardware processor to provide to said user said media.