BACKGROUND Low-resolution images may be acquired in magnetic resonance imaging (MRI) due to limited data acquisition time or other physical constraints, and their resolutions can be improved with super-resolution methods. Since MRI can offer images of an object with different contrasts, e.g., T1-weighted or T2-weighted, the shared information between inter-contrast images can be used to benefit...

We study the problem of evaluating super resolution methods. Traditional evaluation methods usually judge the quality of super resolved images based on a single measure of their difference with the original high resolution images. In this paper, we proposed to use both fidelity (the difference with original images) and naturalness (human visual perception of super resolved images) for evaluatio...

In this paper a new method for multi-frame Super-Resolution is proposed. Having a low resolution(LR) video and a few high resolution(HR) images from a specific scene is frequently occurred. In addition it is usual that between images and video frames there is some differences, because of different of exposure time, moving objects, camera movement and so on. In the proposed method a Super-Resolu...

Super-resolution (SR) image reconstruction is the process ofcombining several low resolution images into a single higherresolution image or Generating high resolution image from a single low resolution image. There is a driving need for digital images ofhigher resolutions and quality.In order to improvethe resolution and perceptual quality of such web image/video, webring forward a sensible sol...

Hyper-Resolution, a new technique for super-resolution reconstruction of images, is based on matching lowresolution target image details to their high-resolution counterparts from an image database. Central to the algorithm is a novel transform of image content from the orthogonal pixel space to a parametric space structured around edges. This approach offers improved quality, more flexibility ...

Super-resolution seeks to create a high-quality image of a scene from several lowquality images of the same scene. Though a literature of super-resolution applications exists, implementing super resolution successfully is apparently quite difficult. In fact, a student unsuccessfully attempted to implement super-resolution in a previous offering of this course. I will attempt the same task, but ...

Term “super-resolution” is typically used for a high-resolution image produced from several low-resolution noisy observations. In this paper, we consider the problem of high-quality interpolation of a single noise-free image. Several aspects of the corresponding super-resolution algorithm are investigated: choice of regularization term, dependence of the result on initial approximation, converg...

this project describes the steps to process a Bayer raw sensor output image which is noisy, undersampled, and blurred. The final output is a de-noised, de-blurred, and upsampled version of the input image. Some of the in-between steps include lens shading correction, color balancing, demosaicing, color correction, etc. Keywords—raw image ; deblurring ; denoising ; image deconvolution ;

Digital Infrared Thermal Imaging, Thermal Imaging or Thermography, could be the next chapter in safer, more effective screening for cancer, sport injuries including orthopedic issues and more. Unfortunately, thermal image camera resolution is considerably lower than of optical cameras, mostly only 160x120 or 320x240 pixels. The readout durability was still poor and needed improvement. In this p...