WebDictionary Learning 130 papers with code • 0 benchmarks • 6 datasets Dictionary Learning is an important problem in multiple areas, ranging from computational neuroscience, machine learning, to computer vision and image processing. The general goal is to find a good basis for given data. Webdecompression transformer super-resolution image-denoising image-restoration restoration denoising image-super-resolution low-level-vision deblocking vision …
Semi-coupled dictionary learning with applications to image super …
Web3D depth cameras have become more and more popular in recent years. However, depth maps captured by these cameras can hardly be used in 3D reconstruction directly … WebJun 1, 2024 · A novel multiclass dictionary learning method is proposed, in which depth image is divided into classified patches according to their geometrical directions and a sparse dictionary is trained within each class, which outperforms state-of-the-art methods in depth map super-resolution in terms of both subjective quality and objective quality. … cherlynn healthcare center
Low-Dose Computed Tomography Image Super …
WebJun 1, 2024 · In recent years, the rapid development of deep learning in the field of multimedia processing, deep learning based super-resolution images restoration has … WebAiming at reducing computed tomography (CT) scan radiation while ensuring CT image quality, a new low-dose CT super-resolution reconstruction method based on combining a random forest with coupled dictionary learning is proposed. The random forest WebMar 22, 2024 · Super-resolution refers to the process of upscaling or improving the details of the image. Follow this blog to learn the options for Super Resolution in OpenCV. When increasing the dimensions of an image, the extra pixels need to be interpolated somehow. cherlyn meaning