Image super-resolution is the problem of recovering a high resolution (hi-res) image from multiple low resolution (lo-res) acquisitions of a scene. The main focus and the most significant contributions of research in this area have been on the problem of super-resolving single channel (grayscale) images. Multi-channel (color) image super-resolution is often treated as an extension to grayscale ...

Image resolution can be improved when the relative displacements in image sequences is known accurately, and some knowledge of the imaging process is available. The proposed approach is similar to back-projection used in tomography. Examples of improved image resolution are given, with computation of the unknown image displacements.

Recognition of document images have important applications in restoring old and classical texts. The problem involves quality improvement before passing it to a properly trained OCR to get accurate recognition of the text. The image enhancement and quality improvement constitute important steps as subsequent recognition depends upon the quality of the input image. There are scenarios when high ...

Undersampling and aliasing occurs frequently in many imaging systems leading to degradation of image quality. Super-resolution attempts to reconstruct a high-resolution image by fusing the incomplete scene information contained in the sequence of under-sampled images. This paper investigates iterative approaches to super-resolution. We propose algorithm that utilises a relatively small number o...

Super-resolution is a technique of producing a high-resolution (HR) image from one or more lowresolution (LR) images. Classical interpolation based magnification techniques like nearest-neighbor, bilinear and bicubic interpolation results in a larger image along with undesirable artifacts like blurring, aliasing and ringing effects. So the aim of super-resolution is to provide a larger image wi...

In this paper a novel technique for Neighbor embedding single image super resolution (SR) is proposed. Given a low-resolution image, its high-resolution image is reconstructed from a set of training images, which are composed of one or more low-resolution and corresponding highresolution image pairs. In this paper we propose a new approach to a single image super-resolution through neighbor emb...

379  Abstract— The Iterative back-projection (IBP) is a classical super-resolution method with low computational complexity that can be applied in real time applications. This paper presents an effective novel single image super resolution approach to recover a high resolution image from a single low resolution input image. The approach is based on an Iterative back projection (IBP) method com...

We propose a vortex-like metamaterial device that is capable of transferring image along a spiral route without losing subwavelength information of the image. The super-resolution image can be guided and magnified at the same time with one single design. Our design may provide insights in manipulating super-resolution image in a more flexible manner. Examples are given and illustrated with nume...

Unmanned aerial vehicles (UAVs or drones) are a very promising branch of technology, and they have been utilized in agriculture-in cooperation with image processing technologies-for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of ...

Single-image super-resolution is of great importance for vision applications, and numerous algorithms have been proposed in recent years. Despite the demonstrated success, these results are often generated based on different assumptions using different datasets and metrics. In this paper, we present a systematic benchmark evaluation for state-of-the-art single-image super-resolution algorithms....