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US 9,519,956 B2Granted
Processing stereo images
AssigneeNokia Technologies Oy
InventorsChing-Hui Chen, Hui Zhou, Timo Ahonen
Life of this patent
Estimating the term…
Abstract
A method comprises estimating disparity values for pixels located in an occluded region of a first one of a defocused pair of stereo images using: a first set of blur map data corresponding to the first one of the defocused pair of stereo images; a first set of disparity map data corresponding to the first one of the defocused pair of stereo images; and a first set of occlusion map data corresponding to the first one of the defocused pair of stereo images.
Claims38
A method comprising:
- estimating disparity values for pixels located in an occluded region of a first one of a defocused pair of stereo images using:
- a first set of blur map data corresponding to the first one of the defocused pair of stereo images;
- a first set of disparity map data corresponding to the first one of the defocused pair of stereo images;
- and
- a first set of occlusion map data corresponding to the first one of the defocused pair of stereo images;
- and
- generating a first set of blur-disparity map data corresponding to the first one of the defocused pair of stereo images, the first set of blur-disparity map data being generated based on:
- the first set of disparity map data;
- the first set of occlusion map data;
- and
- the first set of blur map data,
- wherein each pixel in the first set of blur-disparity map data has an associated mean blur value, and wherein estimating the disparity values for the pixels located in the occluded region of the first one of the defocused pair of stereo images comprises:
- using the first set of occlusion map data to identify at least one occluded pixel in the first set of blur-disparity map data;
- and
- for each occluded pixel in the first set of blur-disparity map data:
- calculating a combined difference between the mean blur value of the occluded pixel and the mean blur value of each non-occluded pixel in the first set of blur-disparity map data within an M×N neighbourhood of the occluded pixel;
- for each mean blur value within the M×N neighbourhood, calculating the mean blur difference;
- and
- identifying the mean blur value having the lowest mean blur difference, wherein the estimated disparity value for the occluded pixel is the disparity value which corresponds to the mean blur value having the lowest mean blur difference.
16 more elements
An apparatus comprising:
- at least one processor;
- and
- at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to:
- estimate disparity values for pixels located in an occluded region of a first one of a defocused pair of stereo images using:
- a first set of blur map data corresponding to the first one of the defocused pair of stereo images;
- a first set of disparity map data corresponding to the first one of the defocused pair of stereo images;
- and
- a first set of occlusion map data corresponding to the first one of the defocused pair of stereo images;
- and
- generate a first set of blur-disparity map data corresponding to the first one of the defocused pair of stereo images, the first set of blur-disparity map data being generated based on:
- the first set of disparity map data;
- the first set of occlusion map data;
- and
- the first set of blur map data,
- wherein each pixel in first set of blur-disparity map data has an associated mean blur value, and wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to estimate the disparity values for the pixels located in the occluded region of the first one of the defocused pair of stereo images by:
- using the first set of occlusion map data to identify at least one occluded pixel in the first set of blur-disparity map data;
- and
- for each occluded pixel in the first set of blur-disparity map data:
- calculating a combined difference between the mean blur value of the occluded pixel and the mean blur value of each non-occluded pixel in the first set of blur-disparity map data within an M×N neighbourhood of the occluded pixel;
- for each mean blur value within the M×N neighbourhood, calculating the mean blur difference;
- and
- identifying the mean blur value having the lowest mean blur difference, wherein the estimated disparity value for the occluded pixel is the disparity value which corresponds to the mean blur value having the lowest mean blur difference.
19 more elements
A non-transitory computer-readable storage medium having stored thereon computer-readable code, which, when executed by computing apparatus, causes the computing apparatus to perform a method comprising:
- estimating disparity values for pixels located in an occluded region of a first one of a defocused pair of stereo images using:
- a first set of blur map data corresponding to the first one of the defocused pair of stereo images;
- a first set of disparity map data corresponding to the first one of the defocused pair of stereo images;
- and
- a first set of occlusion map data corresponding to the first one of the defocused pair of stereo images;
- and
- generating a first set of blur-disparity map data corresponding to the first one of the defocused pair of stereo images, the first set of blur-disparity map data being generated based on:
- the first set of disparity map data;
- the first set of occlusion map data;
- and
- the first set of blur map data,
- wherein each pixel in the first set of blur-disparity map data has an associated mean blur value, and wherein estimating the disparity values for the pixels located in the occluded region of the first one of the defocused pair of stereo images comprises:
- using the first set of occlusion map data to identify at least one occluded pixel in the first set of blur-disparity map data;
- and
- for each occluded pixel in the first set of blur-disparity map data:
- calculating a combined difference between the mean blur value of the occluded pixel and the mean blur value of each non-occluded pixel in the first set of blur-disparity map data within an M×N neighbourhood of the occluded pixel;
- for each mean blur value within the M×N neighbourhood, calculating the mean blur difference;
- and
- identifying the mean blur value having the lowest mean blur difference, wherein the estimated disparity value for the occluded pixel is the disparity value which corresponds to the mean blur value having the lowest mean blur difference.
16 more elements
Dependencies are inferred from the claim text.