IMAGE UPSAMPLING WITH TRAINING IMAGES
First Claim
1. A method of upsampling an image, the method comprising:
- constructing a coarse high-frequency component from a low-resolution, full-frequency image, the coarse high-frequency component comprising a plurality of inferred first-tier high-frequency patches obtained from an existing knowledge base;
constructing a high-compatibility component from the low-resolution, full-frequency image without using the existing knowledge base;
combining the high-compatibility component with the coarse high-frequency component to yield an enhanced high-frequency component, the enhanced high-frequency component comprising a plurality of enhanced high-frequency patches;
constructing an improved high-frequency component from the enhanced high-frequency component, the improved high-frequency component comprising a plurality of inferred third-tier high-frequency patches obtained from the existing knowledge base; and
blending the improved high-frequency component with a high-resolution, low-frequency image, interpolated from the low-resolution, full-frequency image, to yield a high-resolution image.
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Accused Products
Abstract
Images are upsampled using a knowledge base derived from a plurality of high-quality training images. The knowledge base is used to refine a high-frequency component including high-frequency aspects of a high-resolution, low-frequency image, interpolated from a low-resolution full-frequency image, into a high-frequency component. An enhancement step is performed without using a knowledge base to construct a high-compatibility component from the low-resolution, full-frequency image. The low-resolution, full-frequency image is combined with the coarse high-frequency component to yield an enhanced high-frequency component. A second knowledge base step is performed to construct an improved high-frequency component from the enhanced high-frequency component. The improved high-frequency component is blended with a high-resolution, low-frequency image to yield a high-resolution image.
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Citations
20 Claims
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1. A method of upsampling an image, the method comprising:
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constructing a coarse high-frequency component from a low-resolution, full-frequency image, the coarse high-frequency component comprising a plurality of inferred first-tier high-frequency patches obtained from an existing knowledge base; constructing a high-compatibility component from the low-resolution, full-frequency image without using the existing knowledge base; combining the high-compatibility component with the coarse high-frequency component to yield an enhanced high-frequency component, the enhanced high-frequency component comprising a plurality of enhanced high-frequency patches; constructing an improved high-frequency component from the enhanced high-frequency component, the improved high-frequency component comprising a plurality of inferred third-tier high-frequency patches obtained from the existing knowledge base; and blending the improved high-frequency component with a high-resolution, low-frequency image, interpolated from the low-resolution, full-frequency image, to yield a high-resolution image. - View Dependent Claims (2, 3, 4, 5)
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6. A method of upsampling an image using an existing knowledge base, the existing knowledge base including a plurality of patch pairs derived from a set of high-resolution training images, each patch pair including a candidate high-frequency patch representing high-frequency aspects of a plurality of neighboring pixels and a corresponding candidate low-frequency patch representing low-frequency aspects of the plurality of neighboring pixels, the method comprising:
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interpolating a low-resolution, full-frequency image into a high-resolution, low-frequency image; decomposing the high-resolution, low-frequency image into a low-frequency component comprising one or more low-frequency primitives; defining for each low-frequency primitive, a sample low-frequency patch including the low-frequency primitive; identifying for each sample low-frequency patch a plurality of corresponding candidate low-frequency patches from the existing knowledge base, and for each candidate low-frequency patch selecting from its patch pair an associated candidate high-frequency patch; identifying for each sample low-frequency patch an inferred first-tier high-frequency patch selected from the corresponding candidate high-frequency patches; constructing a coarse high-frequency component comprising the inferred first-tier high-frequency patches; constructing a high-compatibility component from the low-resolution, full-frequency image without using the existing knowledge base; combining the high-compatibility component with the coarse high-frequency component to yield an enhanced high-frequency component, the enhanced high-frequency component comprising a plurality of enhanced high-frequency patches; identifying for each enhanced high-frequency patch a plurality of corresponding candidate high-frequency patches from the existing knowledge base; identifying for each enhanced high-frequency patch an inferred third-tier high-frequency patch selected from the corresponding candidate high-frequency patches; constructing an improved high-frequency component comprising the inferred third-tier high-frequency patches; and blending the improved high-frequency component with the high-resolution, low-frequency image to yield a high-resolution image. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A method of using a high-resolution, high-frequency image including a plurality of high-frequency patches in an upsampling process, the method comprising:
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identifying for each high-frequency patch a set of corresponding candidate high-frequency patches from an existing knowledge base; selecting from each set of candidate high-frequency patches, an inferred high-frequency patch; and constructing an improved high-frequency component comprising the inferred high-frequency patches.
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Specification