Image Upsampling using Global and Local Constraints
AssigneeMitsubishi Electric Research Laboratories, Inc.
InventorsOncel Tuzel, Yuichi Taguchi
Life of this patent
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Abstract
A method upsamples an image using a non-linear fully connected neural network to produce only global details of an upsampled image and interpolates the image to produce a smooth upsampled image. The method concatenates the global details and the smooth upsampled image into a tensor and applies a sequence of nonlinear convolutions to the tensor using a convolutional neural network to produce the upsampled image.
Claims20
A method for upsampling an image, comprising:
- upsampling the image using a non-linear fully connected neural network to produce only global details of an upsampled image;
- interpolating the image to produce a smooth upsampled image;
- concatenating the global details and the smooth upsampled image into a tensor;
- and
- applying a sequence of nonlinear convolutions to the tensor using a convolutional neural network to produce the upsampled image, wherein steps of the method are performed by a processor.
A computer system for upsampling an image including a processor and a memory, wherein the instructions stored in the memory configure the processor to
- upsample the image using a non-linear fully connected neural network to produce only global details of an upsampled image;
- interpolate the image to produce a smooth upsampled image;
- concatenate the global details and the smooth upsampled image into a tensor;
- and
- apply a sequence of nonlinear convolutions to the tensor using a convolutional neural network to produce the upsampled image.
Dependencies are inferred from the claim text.