Dynamic PET Image Denoising Using Deep Image Prior Combined With Regularization by Denoising
نویسندگان
چکیده
منابع مشابه
Deep Learning for Image Denoising
Deep learning is an emerging approach for finding concise, slightly higher level representations of the inputs, and has been successfully applied to many practical learning problems, where the goal is to use large data to help on a given learning task. We present an algorithm for image denoising task defined by this model, and show that by training on large image databases we are able to outper...
متن کاملDenoising Prior Driven Deep Neural Network for Image Restoration
Deep neural networks (DNNs) have shown very promising results for various image restoration (IR) tasks. However, the design of network architectures remains a major challenging for achieving further improvements. While most existing DNN-based methods solve the IR problems by directly mapping low quality images to desirable high-quality images, the observation models characterizing the image deg...
متن کاملDENOISING AN IMAGE BY DENOISING ITS CURVATURE IMAGE By
In this article we show that when an image is corrupted by additive noise, its curvature image is less affected by it, i.e. the PSNR of the curvature image is larger. We conjecture that, given a denoising method, we may obtain better results by applying it to the curvature image and then reconstructing from it a clean image, rather than denoising the original image directly. Numerical experimen...
متن کاملDenoising an Image by Denoising Its Curvature Image
In this article we argue that when an image is corrupted by additive noise, its curvature image is less affected by it, i.e. the PSNR of the curvature image is larger. We speculate that, given a denoising method, we may obtain better results by applying it to the curvature image and then reconstructing from it a clean image, rather than denoising the original image directly. Numerical experimen...
متن کاملA New Shearlet Framework for Image Denoising
Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed. In Bayesshrink method, sharp features are preserved. However, PSNR (Peak Signal-to-Noise Ratio) is considerably low. BLS-GSM generates some discontinuous information during the course of denoising a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: 2169-3536
DOI: 10.1109/access.2021.3069236