Apparatus, method and program for image processing

• US 20060291739A1
• Filed: 06/26/2006
• Published: 12/28/2006
• Est. Priority Date: 06/24/2005
• Status: Abandoned Application

• Current Assignee: Fujifilm Corporation (Fujifilm Holdings Corporation)
• Original Assignee: Fuji Photo Film Co Limited (Fujifilm Holdings Corporation)
• Inventors: Ito, Wataru, Li, Yuanzhong
• Application Number:
  US11/474,294
• Publication Number:
  US 20060291739A1
• Time in Patent Office: Days
• US Class Current: 382/254
• CPC Class Codes: G06V 10/30 Noise filtering
• CPC Class Codes: G06V 10/7557 based on appearance, e.g. active appearance models [AAM]
• CPC Class Codes: G06V 40/165 using facial parts and geometric relationships

Abstract

Graininess reduction processing is carried out with accuracy by finding a degree of graininess in an image. For this purpose, a parameter acquisition unit obtains a weighting parameter for a principal component representing the degree of graininess in a face region found in the image by a face detection unit, by fitting to the face region a mathematical model generated by a method of AAM using a plurality of sample images representing human faces in different degrees of graininess. A parameter changing unit changes the parameter to have a desired value. A graininess reduction unit reduces graininess of the face region according to the parameter having been changed.

Claims

1. An image processing apparatus comprising:

parameter acquisition means for obtaining a weighting parameter for a statistical characteristic quantity representing a degree of graininess in a predetermined structure in an input image by fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure in different degrees of graininess, and the model representing the structure by one or more statistical characteristic quantities including the statistical characteristic quantity representing the degree of graininess and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure;

parameter changing means for changing a value of the weighting parameter obtained by the parameter acquisition means to a desired value; and

graininess reduction means for reducing graininess of the structure in the input image according to the weighting parameter having been changed.

2. The image processing apparatus according to claim 1, wherein the predetermined structure is a human face.

3. The image processing apparatus according to claim 1 further comprising detection means for detecting the structure in the input image, wherein

the parameter acquisition means obtains the weighting parameter by fitting the model to the structure having been detected.

4. The image processing apparatus according to claim 1 further comprising selection means for obtaining a property of the structure in the input image and for selecting the model corresponding to the property from a plurality of the models representing the predetermined structure for respective properties of the structure, wherein

the parameter acquisition means obtains the weighting parameter by fitting the selected model to the structure.

5. An image processing apparatus comprising:

parameter acquisition means for obtaining a weighting parameter for a statistical characteristic quantity representing a degree of graininess in a predetermined structure in an input image by fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure in different degrees of graininess, and the model representing the structure by one or more statistical characteristic quantities including the statistical characteristic quantity representing the degree of graininess and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure; and

graininess reduction means for reducing graininess in the input image according to a value of the weighting parameter having been obtained by the parameter acquisition means.

6. The image processing apparatus according to claim 5, wherein the predetermined structure is a human face.

7. The image processing apparatus according to claim 5 further comprising detection means for detecting the structure in the input image, wherein

the parameter acquisition means obtains the weighting parameter by fitting the model to the structure having been detected.

8. The image processing apparatus according to claim 5 further comprising selection means for obtaining a property of the structure in the input image and for selecting the model corresponding to the property from a plurality of the models representing the predetermined structure for respective properties of the structure, wherein

the parameter acquisition means obtains the weighting parameter by fitting the selected model to the structure.

9. An image processing apparatus comprising:

reconstruction means for generating a reconstructed image of a predetermined structure in an input image having a grain component by reconstructing an image representing the structure after fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure without a grain component, and the model representing the structure by one or more statistical characteristic quantities and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure;

graininess degree acquisition means for obtaining a degree of graininess in the structure in the input image by calculating a difference value between values of pixels corresponding to each other in the predetermined structure in the reconstructed image and in the input image; and

graininess reduction means for reducing graininess in the input image according to the degree of graininess obtained by the graininess degree acquisition means.

10. The image processing apparatus according to claim 9, wherein the predetermined structure is a human face.

11. The image processing apparatus according to claim 9 further comprising detection means for detecting the structure in the input image, wherein

the reconstruction means generates the reconstructed image by fitting the model to the structure having been detected.

12. The image processing apparatus according to claim 9 further comprising selection means for obtaining a property of the structure in the input image and for selecting the model corresponding to the property from a plurality of the models representing the predetermined structure for respective properties of the structure, wherein

the reconstruction means generates the reconstructed image by fitting the selected model to the structure.

13. An image processing method comprising the steps of:

obtaining a weighting parameter for a statistical characteristic quantity representing a degree of graininess in a predetermined structure in an input image by fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure in different degrees of graininess, and the model representing the structure by one or more statistical characteristic quantities including the statistical characteristic quantity representing the degree of graininess and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure; and

changing a value of the weighting parameter to a desired value; and

reducing graininess of the structure in the input image according to the weighting parameter having been changed.

14. An image processing method comprising the steps of:

obtaining a weighting parameter for a statistical characteristic quantity representing a degree of graininess in a predetermined structure in an input image by fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure in different degrees of graininess, and the model representing the structure by one or more statistical characteristic quantities including the statistical characteristic quantity representing the degree of graininess and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure; and

reducing graininess in the input image according to a value of the weighting parameter having been obtained.

15. An image processing method comprising the steps of:

generating a reconstructed image of a predetermined structure in an input image having a grain component by reconstructing an image representing the structure after fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure without a grain component, and the model representing the structure by one or more statistical characteristic quantities and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure;

obtaining a degree of graininess in the structure in the input image by calculating a difference value between values of pixels corresponding to each other in the predetermined structure in the reconstructed image and in the input image; and

reducing graininess in the input image according to the degree of graininess having been obtained.

16. An image processing program for causing a computer to function as:

parameter acquisition means for obtaining a weighting parameter for a statistical characteristic quantity representing a degree of graininess in a predetermined structure in an input image by fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure in different degrees of graininess, and the model representing the structure by one or more statistical characteristic quantities including the statistical characteristic quantity representing the degree of graininess and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure;

parameter changing means for changing a value of the weighting parameter obtained by the parameter acquisition means to a desired value; and

graininess reduction means for reducing graininess of the structure in the input image according to the weighting parameter having been changed.

17. An image processing program for causing a computer to function as:

parameter acquisition means for obtaining a weighting parameter for a statistical characteristic quantity representing a degree of graininess in a predetermined structure in an input image by fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure in different degrees of graininess, and the model representing the structure by one or more statistical characteristic quantities including the statistical characteristic quantity representing the degree of graininess and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure; and

graininess reduction means for reducing graininess in the input image according to a value of the weighting parameter having been obtained by the parameter acquisition means.

18. An image processing program for causing a computer to function as:

reconstruction means for generating a reconstructed image of a predetermined structure in an input image having a grain component by reconstructing an image representing the structure after fitting a model representing the structure to the structure in the input image, the model having been obtained by carrying out predetermined statistical processing on a plurality of images representing the predetermined structure without a grain component, and the model representing the structure by one or more statistical characteristic quantities and by weighting parameter or parameters for weighting the statistical characteristic quantity or quantities according to an individual characteristic of the structure;

graininess degree acquisition means for obtaining a degree of graininess in the structure in the input image by calculating a difference value between values of pixels corresponding to each other in the predetermined structure in the reconstructed image and in the input image; and

graininess reduction means for reducing graininess in the input image according to the degree of graininess obtained by the graininess degree acquisition means.