首页addersr: towards energy efficient image super-resolution

addersr: towards energy efficient image super-resolution

时间: 2023-04-23 21:05:22 浏览: 194

Image super-resolution

图像超分辨深度学习 cnn Abstract. We propose a deep learning method for single image super- resolution (SR). Our method directly learns an end-to-end mapping be- tween the low/high-resolution images. The mapping is represented as a deep convolutional neural network (CNN) [15] that takes the low- resolution image as the input and outputs the high-resolution one. We further show that traditional sparse-coding-based SR methods can also be viewed as a deep convolutional network. But unlike traditional meth- ods that handle each component separately, our method jointly optimizes all layers. Our deep CNN has a lightweight structure, yet demonstrates state-of-the-art restoration quality, and achieves fast speed for practical on-line usage.

能源高效的图像超分辨率技术图像超分辨率技术是一种将低分辨率图像转换为高分辨率图像的方法。然而，这种技术需要大量的计算资源，因此需要能源高效的方法来实现。近年来，研究人员提出了许多能源高效的图像超分辨率技术，包括基于深度学习的方法、基于稀疏编码的方法和基于图像统计的方法等。这些方法可以减少计算资源的使用，从而实现能源高效的图像超分辨率。

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