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.
The goal of image filtering is to remove the noise from the image in such a way that the "original" image is visible. Image filtering is a method by which we can enhance images .Image filtering methods are applied on images to remove the different types of noise that are either present in the image during capturing or injected into the image during transmission. Fuzzy Filter method for image de-noising based on Fuzzy set theory. This filter employs Fuzzy rules for deciding the gray level of a pixel within a window in the image. The Mean Filter is a linear filter which uses a mask over each pixel in the signal. Each of the components of the pixels which fall under the mask are averaged together to form a single pixel. This filter is also called as average filter. In these work Gaussian noise used and image filtering performed by fuzzy filter and mean filter. Further results have been compared for filters using Standard Deviation and Peak Signal to Noise Ratio.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.