摘要:
A motion-vector-setting section (31) sets a motion vector in units of pixel in a target image. Based on the motion vector, a target-pixel-setting section (35) sets a target pixel for each image in plural images to be processed. A motion-blur-amount-setting section (33) sets a motion blur amount in units of pixel based on the motion vector and the exposure-time ratio set in units of image in the exposure-time-ratio-setting section (32). A processing-region-setting section (36) sets processing regions corresponding to the target pixel for each of the plural images based on the motion blur amount. A processing-coefficient-setting section (37) sets processing coefficients based on the motion blur amount. A pixel-value-generating section (38) generates motion-blur-removed pixel values that correspond to the target pixel by linear combination of pixel values corresponding to pixels in the processing region and the processing coefficients, so that they can be output from an integration section (39) as one pixel value. By utilizing any time-directional information significantly, motion-blur-removing processing can be accurately performed.
摘要:
A shooting-information-detecting section (31) detects shooting information from an image pick-up section (10). A motion-detecting section (33) detects a motion direction of an image on an overall screen based on a motion direction of the image pick-up section contained in the shooting information. A processing-region-setting section (36) sets a processing region in at least any one of a predicted target image and a peripheral image thereof, which correspond to a target pixel in the predicted target image. A processing-coefficient-setting section (37) sets a motion-blur-removing-processing coefficient that corresponds to the motion direction detected in the motion-detecting section (33). A pixel-value-generating section (38) generates a pixel value that corresponds to the target pixel based on a pixel value of a pixel in the processing region set in the processing-region-setting section (36) and the processing coefficient set in the processing-coefficient-setting section (37). Motion-blur-removing processing can be accurately performed.
摘要:
A motion-setting section (61) sets a motion amount and a motion direction for obtaining processing coefficients. A student-image-generating section (62) generates student images obtained by adding a motion blur to a teacher image not only based on the set motion amount and the set motion direction but also by changing at least one of the motion amount and motion direction in a specific ratio and student images obtained by adding no motion blur to the teacher image. A prediction-tap-extracting section (64) extracts, in order to extract a main term that mainly contains component of the target pixel, at least a pixel value of pixel in the student image whose space position roughly agrees with space position of the target pixel in the teacher image. A processing-coefficient-generating section (65) generates processing coefficients for predicting the target pixels in the teacher images from the pixel values of extracted pixels based on a relationship between the pixels thus extracted and the target pixels in the teacher images. The processing coefficients that are suitable for any motion blur removing which is robust against any shift of the motion vector can be generated through learning.
摘要:
A target-pixel-setting section (31) sets a target pixel in a target image to be predicted. A motion-direction-detecting section (32) detects a motion direction corresponding to the target pixel. A pixel-value-extracting section (36) extracts from peripheral images corresponding to the target image, in order to extract a main term that mainly contains component of the target pixel in a moving object that encounters a motion blur in the peripheral images, at least pixel values of pixels in the peripheral images whose space position roughly agree with space position of the target pixel. A processing-coefficient-setting section (37a) sets a specific motion-blur-removing-processing coefficient. A pixel-value-generating section (38a) newly generates pixel values for processing from the pixel values extracted by the pixel-value-extracting section (36) corresponding to the motion direction and generates pixel values corresponding to the target pixel based on the pixel values for processing and the specific motion-blur-removing-processing coefficients. It is possible to perform a robust motion-blur-removing processing on any shifts of motion vector.
摘要:
A coefficient learning apparatus includes: a student-image generation section configured to generate a student image from the teacher image; a class classification section configured to sequentially set each of pixels in the teacher image as a pixel of interest and generate a class for the pixel of interest from the values of a plurality of specific pixels; a weight computation section configured to add up feature quantities; and a processing-coefficient generation section configured to generate a prediction coefficient on the basis of a determinant including said deterioration equation and a weighted constraint condition equation.
摘要:
A motion-vector-setting section (31) sets a motion vector in units of pixel in a target image. Based on the motion vector, a target-pixel-setting section (35) sets a target pixel for each image in plural images to be processed. A motion-blur-amount-setting section (33) sets a motion blur amount in units of pixel based on the motion vector and the exposure-time ratio set in units of image in the exposure-time-ratio-setting section (32). A processing-region-setting section (36) sets processing regions corresponding to the target pixel for each of the plural images based on the motion blur amount. A processing-coefficient-setting section (37) sets processing coefficients based on the motion blur amount. A pixel-value-generating section (38) generates motion-blur-removed pixel values that correspond to the target pixel by linear combination of pixel values corresponding to pixels in the processing region and the processing coefficients, so that they can be output from an integration section (39) as one pixel value. By utilizing any time-directional information significantly, motion-blur-removing processing can be accurately performed.
摘要:
A coefficient learning apparatus includes: a student-image generation section configured to generate a student image from the teacher image; a class classification section configured to sequentially set each of pixels in the teacher image as a pixel of interest and generate a class for the pixel of interest from the values of a plurality of specific pixels; a weight computation section configured to add up feature quantities; and a processing-coefficient generation section configured to generate a prediction coefficient on the basis of a determinant including said deterioration equation and a weighted constraint condition equation.
摘要:
A motion-vector-setting section (31) sets a first motion vector in units of pixel in a target image. An exposure-time-ratio-setting section (32) sets in units of image an exposure time ratio that is a ratio between a time interval of the target image and a period of exposure time. A motion-blur-amount-setting section (33) sets a motion blur amount in units of pixel based on the exposure time ratio and the first motion vector. Based on the motion amount, a processing-region-setting section (36) sets processing regions as well as a processing-coefficient-setting section (37) sets processing coefficients. A pixel-value-generating section (38) generates pixel values that correspond to the target pixel from pixel values in the processing region and the processing coefficients. A motion-blur-adding section (41) adds a motion blur to an image containing the pixel value generated based on an input second motion vector and the first motion vector. An image-moving section (42) moves the motion-blur-added image along a counter vector of the second motion vector. Any more real arbitrary viewpoint image can be generated.
摘要:
A motion determining apparatus for detecting a motion of a partial picture of an input picture signal is disclosed, that comprises a first motion detecting portion for comparing a frame difference detected for the partial picture with a predetermined threshold value and determining that the partial picture has a motion when the frame difference is larger than the threshold value, a second motion detecting portion for comparing a frame difference detected for the partial picture with a predetermined threshold value, comparing a field difference detected for the partial picture with a predetermined threshold value, and determining that there is a motion of an artificial picture when the frame difference and the field difference are larger than the respective threshold values, and an output portion for forming motion determination data with determination data that is output from the first motion detecting portion and the second motion detecting portion.
摘要:
A motion determining apparatus for detecting a motion of a partial picture of an input picture signal is disclosed, that comprises a first detecting means for detecting a frame difference of the partial picture, a second detecting means for detecting a spatial activity of the partial picture, a threshold value generating means for generating a first threshold value, a second threshold value, and a third threshold value, a comparing means having at least a first comparing portion for comparing the frame difference detected by said first detecting means with the first threshold value and a second comparing portion for comparing the frame difference detected by said first detecting means with the second threshold value, a third comparing means for comparing the spatial activity detected by said second detecting means with the third threshold value, and a motion class determining means for receiving the compared results of said first comparing portion, said second comparing portion, and said third comparing means and determining the motion of the partial picture in at least three levels.