yu4u/noise2noise
An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"
This tool helps improve the quality of images by removing various types of noise, such as static, text, or impulse artifacts. It takes noisy images as input and produces clearer, denoised versions, even without requiring perfectly clean reference images for training. It's designed for researchers and practitioners working with image processing and computer vision applications who need to clean up imperfect image data.
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Use this if you need to remove noise from images and traditional denoising methods are difficult to apply due to the lack of clean, pristine reference images for training.
Not ideal if you already have access to a large dataset of perfectly clean images paired with their noisy counterparts, as standard denoising methods might offer superior results.
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Python
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MIT
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Aug 12, 2021
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