Image Resolution Enhancement Using Convolutional Autoencoders

Abstract

Resolution is an important characteristic to determine the nature and features of the image. Enhancing the resolution strengthens the features hidden within the image, and make the image sharper and more informative. The image quality is improved when noise is removed/suppressed from it. The proposed model provides a technique to enhance the resolution of different types of images, obtained from imaging devices, using a convolutional autoencoder. A convolutional neural network (CNN) architecture is developed by adding different layers to the neural network. An autoencoder capable of encoding and decoding the structure of the images is proposed to enhance their resolution. The model tends to learn the lower-dimensional features of unclear images and provide a high resolution to them by predicting and enhancing their dimensions. The model is trained on low-resolution images and the corresponding high-resolution images, and a convolutional auto-encoder is implemented to denoise the image to introduce highresolution in the blurred or corrupted images. The model overcomes the limitations of the existing denoising filter techniques and provides a higher level of image quality enhancement.

A Monthly Rainfall Forecasting from Sea Surface Temperature Spatial Pattern

“…In this work, the encoder is applied to the original image. Then, the original image is represented in smaller feature vectors image or it is compressed [13]. • The decoder as shown in Figure 4 is an algorithm used for image decompression.…”

“…The important features of the original image are not lost after the decoding process is applied in the encoded image. The compressed image is returned to its original image [13].…”

“…The convolutional autoencoder aims to predict monthly rainfall from the Sea Surface Temperature images. The rainfall predictor is implemented by adding the following layers to the neural network as described in Table 2 [13]. There is a procedure as the following:…”