Machine learning based image processing techniques
AssigneeOutward, Inc.
InventorsClarence Chui, Manu Parmar
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Abstract
A machine learning based image processing architecture and associated applications are disclosed herein. In some embodiments, a machine learning framework is trained to learn low level image attributes such as object/scene types, geometries, placements, materials and textures, camera characteristics, lighting characteristics, contrast, noise statistics, etc. Thereafter, the machine learning framework may be employed to detect such attributes in other images and process the images at the attribute level.
Claims20
A method, comprising:
- receiving an input image;
- filtering the received input image with a set of one or more filters identified using a machine learning framework;
- and
- outputting an output image comprising a denoised version of the input image.
A system, comprising:
- a processor configured to:
- receive an input image;
- filter the received input image with a set of one or more filters identified using a machine learning framework;
- and
- output an output image comprising a denoised version of the input image;
- and
- a memory coupled to the processor and configured to provide the processor with instructions.
A computer program product embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
- receiving an input image;
- filtering the received input image with a set of one or more filters identified using a machine learning framework;
- and
- outputting an output image comprising a denoised version of the input image.
Dependencies are inferred from the claim text.