The majority of applications requiring high resolution images to derive and analyze data accurately and easily. Image super resolution is playing an effective role in those applications. Image super resolution is the process of producing high resolution image from low resolution image. In this paper, we study various image super resolution techniques with respect to the quality of results and p...

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 of signals and images can improve the automatic detection and recognition of objects of interest. However, the uncertainty associated with this process is not often taken into consideration. This is important because the processing of noisy signals can result in spurious estimates of the scene content. This paper reviews a variety of super-resolution techniques and presents two...

In this paper we present a variational, spatiotemporal video super resolution scheme that produces not just one but n high resolution video frames from an n frame low resolution video sequence. We use a generic prior and the output is artifact-free, sharp and superior in quality to state of the art home cinema video processors. Unlike many other super resolution schemes, ours does not limit its...

Texture synthesis has proven successful at imitating a wide variety of textures. Adding additional constraints (in the form of a low-resolution version of the texture to be synthesized) makes it possible to use texture synthesis methods for texture superresolution. The Single-image Superresolution Problem The problem we are trying to solve is the following: Given: a low-resolution image and hig...

A blind single-image super resolution method is proposed to enhance the spatial resolution of the image with defocus blur. Firstly, according to the low resolution imaging model, a framework of blind singleimage super resolution reconstruction is presented. Secondly, utilizing Wiener filtering algorithm, the errorparameter curve of the defocus blurred image was generated, through which the defo...

Multi-frame image super-resolution makes use of a set of low-resolution images to reconstruct one or more high-resolution images. This paper presents a novel super-resolution algorithm that uses perceptually important content characteristics such as edges, texture, and brightness to improve visual quality. The superresolution algorithm introduces perceptually-adaptive constraint relaxation to o...