Application of convolutional neural networks in image super-resolution

• URL: http://arxiv.org/abs/2506.02604v2
• Date: Fri, 06 Jun 2025 13:07:16 GMT
• Title: Application of convolutional neural networks in image super-resolution
• Authors: Chunwei Tian, Mingjian Song, Wangmeng Zuo, Bo Du, Yanning Zhang, Shichao Zhang,
• Abstract summary: convolutional neural networks (CNNs) have become mainstream methods for image super-resolution.<n>There are big differences of different deep learning methods with different types.<n>This paper first introduces principles of CNNs in image super-resolution, then introduces CNNs based bicubic, nearest neighbor, bilinear, transposed convolution, sub-pixel layer, meta-up-sampling for image super-resolution.<n>Finally, this paper gives potential research points and drawbacks and summarizes the whole paper, which can facilitate developments of CNNs in image super-resolution.
• Score: 99.25287909319401
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Due to strong learning abilities of convolutional neural networks (CNNs), they have become mainstream methods for image super-resolution. However, there are big differences of different deep learning methods with different types. There is little literature to summarize relations and differences of different methods in image super-resolution. Thus, summarizing these literatures are important, according to loading capacity and execution speed of devices. This paper first introduces principles of CNNs in image super-resolution, then introduces CNNs based bicubic interpolation, nearest neighbor interpolation, bilinear interpolation, transposed convolution, sub-pixel layer, meta up-sampling for image super-resolution to analyze differences and relations of different CNNs based interpolations and modules, and compare performance of these methods by experiments. Finally, this paper gives potential research points and drawbacks and summarizes the whole paper, which can facilitate developments of CNNs in image super-resolution.

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