Super-resolution reconstruction based on two-stage residual neural network
نویسندگان
چکیده
With the constant update of deep learning technology, super-resolution reconstruction technology based on has also attained a significant breakthrough. This paper primarily discusses integration and techniques. Regarding application in reconstruction, improvement is focused two dimensions algorithm efficiency effect. On basis currently available neural network algorithms, this puts forward two-stage residual structure. Thereinto, mainly embodied modification image feature extraction modules increase block into stages. It experimentally evidenced by simulation that shows certain extent for effect compared with related methods.
منابع مشابه
Residual Dense Network for Image Super-Resolution
A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well. However, most deep CNN based SR models do not make full use of the hierarchical features from the original low-resolution (LR) images, thereby achieving relatively-low performance. In this paper, we propose a novel residual dense network (...
متن کاملTwo-stage network DEA-R based on value efficiency
It is essential for most organizations and financial institutes to be able to evaluate their decision-making units (DMUs), when there is only a ratio of inputs to outputs (or vice versa) available. In this paper, we will propose our two-stage DEA-R models, which are a combination of data envelopment analysis and ratio data, based on value efficiency. Integrating value efficiency into data envel...
متن کاملAccelerating the Super-Resolution Convolutional Neural Network
As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) [1, 2] has demonstrated superior performance to the previous hand-crafted models either in speed and restoration quality. However, the high computational cost still hinders it from practical usage that demands real-time performance (24 fps). In this paper, we aim at accel...
متن کاملDeep Residual Network for Joint Demosaicing and Super-Resolution
In digital photography, two image restoration tasks have been studied extensively and resolved independently: demosaicing and super-resolution. Both these tasks are related to resolution limitations of the camera. Performing superresolution on a demosaiced images simply exacerbates the artifacts introduced by demosaicing. In this paper, we show that such accumulation of errors can be easily ave...
متن کاملMAP-Based Image Super-resolution Reconstruction
From a set of shifted, blurred, and decimated image , super-resolution image reconstruction can get a high-resolution image. So it has become an active research branch in the field of image restoration. . In general, super-resolution image restoration is an ill-posed problem. Prior knowledge about the image can be combined to make the problem well-posed, which contributes to some regularization...
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: Machine learning with applications
سال: 2021
ISSN: ['2666-8270']
DOI: https://doi.org/10.1016/j.mlwa.2021.100162