Mosaicing and super resolution are two ways to combine information from multiple frames in video sequences. Mosaicing displays the information of multiple frames in a single panoramic image. Super-resolution uses regions which appear in multiple frames to improve resolution and reduce noise. The aim of this work is constructing a high resolution mosaic from a video sequence in an efficient way....

We propose a method for super-resolution of range image. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we demonstrate that our recently reported approach which reconstructs dense range images from sparse range data by exploiting a registered colour image, can be applied for the task of resolution enhancement of range images...

the goal of multi-frame super resolution (sr) is to fuse multiple low resolution (lr) images to produce one high resolution (hr) image. the major challenge of classic sr approaches is accurate motion estimation between the frames. to handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels i...

Multi-angle remote sensing images are acquired over the same imaging scene from different angles, and share similar but not identical information. It is therefore possible to enhance the spatial resolution of the multi-angle remote sensing images by the super-resolution reconstruction technique. However, different sensor shooting angles lead to different resolutions for each angle image, which ...

In computer vision field, Image resolution enhancement has become the most current research area. Improving image resolution by applying costly hardware is expensive and time-consuming. In this paper we have discussed different methods to improve the resolution of the single image and we have given a comparison of different Super resolution algorithms for standard images based on PSNR and SSIM ...

Due to the factors like processing power limitations and channel capabilities images are often down sampled and transmitted at low bit rates resulting in a low resolution compressed image. High resolution images can be reconstructed from several blurred, noisy and down sampled low resolution images using a computational process know as super resolution reconstruction. Super-resolution is the pr...

We propose an effective super resolution reconstruction algorithm based on patch similarity and back-projection modification. In the proposed algorithm, we assume patch to be similar in natural images and extract the high-frequency information from the best similar patch to add into goal high-resolution image. In the process of reconstruction, the high-resolution patch is back-projected into th...

Super resolution technology origins from the field of image restoration. The increasing difficulties in the resolution improvement by hardware prompts the super resolution reconstruction that can solve this problem effectively, but the general algorithms of super resolution reconstruction model are unable to quickly complete the image processing. Based on this problem, this paper studies on ada...

Due to the factors like processing power limitations and channel capabilities images are often down sampled and transmitted at low bit rates resulting in a low resolution compressed image. High resolution images can be reconstructed from several blurred, noisy and down sampled low resolution images using a computational process know as super resolution reconstruction. Super-resolution is the pr...

Super resolution technique was first proposed for enhancing the image resolution, and then it was expanded to video sequence for obtaining a higher resolution video from low resolution input. Recently, super-resolution based video coding has emerged as an important research topic as the image resolution increases rapidly and the downsampling coding is very efficient for bit rate reduction. With...