论文标题
拉普拉斯金字塔状的自动编码器
Laplacian Pyramid-like Autoencoder
论文作者
论文摘要
在本文中，我们通过添加Laplacian Pyramid（LP）概念来开发Laplacian类似于类似的自动编码器（LPAE），该概念广泛用于分析信号处理中的图像。 LPAE将图像分解为近似图像和编码器部分中的详细图像，然后尝试使用两个组件在解码器部分中重建原始图像。我们使用LPAE进行分类和超分辨率领域的实验。使用详细图像和较小尺寸的近似图像作为分类网络的输入，我们的LPAE使模型更轻。此外，我们表明连接分类网络的性能仍然很高。在超分辨率区域中，我们表明解码器部分通过设置类似于LP的结构来获得高质量的重建图像。因此，LPAE通过组合自动编码器的解码器和超分辨率网络来改善原始结果。
In this paper, we develop the Laplacian pyramid-like autoencoder (LPAE) by adding the Laplacian pyramid (LP) concept widely used to analyze images in Signal Processing. LPAE decomposes an image into the approximation image and the detail image in the encoder part and then tries to reconstruct the original image in the decoder part using the two components. We use LPAE for experiments on classifications and super-resolution areas. Using the detail image and the smaller-sized approximation image as inputs of a classification network, our LPAE makes the model lighter. Moreover, we show that the performance of the connected classification networks has remained substantially high. In a super-resolution area, we show that the decoder part gets a high-quality reconstruction image by setting to resemble the structure of LP. Consequently, LPAE improves the original results by combining the decoder part of the autoencoder and the super-resolution network.
