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Image Recovery Method Improves Compressive Sensing, Phase Retrieval

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JOEL WILLIAMS, ASSOCIATE EDITOR
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Research from Lawrence Livermore National Laboratory (LLNL) has yielded a method of compressive image recovery that is trained on patches of images, rather than full-size images. The method, called GPP (generative patch prior), is able to recover a wide variety of natural images. It compares favorably with other existing methods, the researchers said, in its ability to perform compressive image sensing and complete compressive phase retrieval tasks. Compressive sensing is a class of methods that aids in designing new image sensors that, rather than sensing individual pixels, sense coded...Read full article

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    Published: February 2021
    Glossary
    computer vision
    Computer vision enables computers to interpret and make decisions based on visual data, such as images and videos. It involves the development of algorithms, techniques, and systems that enable machines to gain an understanding of the visual world, similar to how humans perceive and interpret visual information. Key aspects and tasks within computer vision include: Image recognition: Identifying and categorizing objects, scenes, or patterns within images. This involves training...
    Research & Technologycomputer visioncompression sensingcompressive imagingcompressive sensingcameras image compressionimage compressionimage reconstructionimage reconstruction algorithmimage reconstruction algorithmsPriorpatchpatch priorsgenerative patch priorgenerative patch priorsGPPLawrence LivermoreLawrence Livermore National LabLawrence Livermore National LaboratoryThe News Wire

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