Systems and Methods for Content-Aware Enhancement of Images
AssigneeShinyfields Limited
InventorsDmitry Sytnik, Irina Lisova, Andrey Frolov
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Abstract
Exemplary embodiments are directed to a system for content-aware enhancement of an image. The system includes an interface configured to receive as input an original image, and a processing device in communication with the interface. The processing device is configured to process the original image to detect one or more objects in the original image, generate an in-focus person mask of the original image for one or more in-focus people in the original image, and apply one or more enhancements to areas of the original image excluding the in-focus person mask.
Claims20
A system for content-aware enhancement of an image, the system comprising:
- an interface configured to receive as input an original image;
- and
- a processing device in communication with the interface, the processing device configured to:
- (i) process the original image using a neural network to detect one or more objects in the original image;
- (ii) generate an in-focus person mask of the original image for one or more in-focus people in the original image;
- and
- (iii) apply one or more enhancements to areas of the original image excluding the in-focus person mask.
A method for content-aware enhancement of an image, the method comprising:
- receiving as input at an interface an original image;
- detecting one or more objects in the original image with a neural network;
- generating an in-focus person mask of the original image for one or more in-focus people in the original image;
- and
- applying one or more enhancements to areas of the original image excluding the in- focus person mask.
A non-transitory computer-readable medium storing instructions at least for content- aware enhancement of an image that are executable by a processing device, wherein execution of the instructions by the processing device causes the processing device to:
- receive as input at an interface an original image;
- detect one or more objects in the original image with a neural network;
- generate an in-focus person mask of the original image for one or more in-focus people in the original image;
- and
- apply one or more enhancements to areas of the original image excluding the in-focus person mask.
Dependencies are inferred from the claim text.