NikolasMarkou/blind_image_denoising
Implementing CVPR 2020 paper "ROBUST AND INTERPRETABLE BLIND IMAGE DENOISING VIA BIAS - FREE CONVOLUTIONAL NEURAL NETWORKS"
This library helps anyone working with images to clean up noisy pictures before performing further analysis. It takes in a grayscale or color image that has various types of noise (like static, blur, or pixelation) and outputs a clearer, denoised version. The end-users are typically researchers, engineers, or analysts who rely on high-quality images for tasks like object recognition, medical imaging, or quality inspection.
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Use this if you need to reliably remove different kinds of noise from images to improve the accuracy of subsequent computer vision tasks, especially when interpretability of the denoising process is important.
Not ideal if you are looking for a simple, one-click photo enhancement tool for casual use or if your primary goal is artistic image restoration.
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Jupyter Notebook
License
MIT
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Last pushed
Aug 07, 2024
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