Found inside – Page 97In several application areas such as art, medicine, broadcasting and e- commerce, high-resolution images are needed. Super-resolution is the algorithmic ... Found inside – Page 194There emerge some researches on super resolution of iris images in recent years. ... interpolation is used to reconstruct the high-resolution iris image. Found inside – Page 119The multi-frame super-resolution framework can better be understood through a conceptual degradation model, which shows how an unknown high-resolution image ... Found inside – Page 113217-226, 2002. doi:10.1 109/76.999200 [4] L. D. Alvarez, J. Mateos, R. Molina, and A. K. Katsaggelos, "High resolution images from compressed low resolution ... Found inside – Page 551Super-resolution image restoration is a process of back stepping calculating the original high-resolution image from the series low-resolution observed ... Explore some of the most mysterious objects in space, powerful black holes that extinguish light and intense quasars that outshine an entire galaxy. Found inside – Page 497The super-resolution problem is posed as learning the mapping between pairs of low-resolution and high-resolution image patches. Found inside – Page xviMultiframe Super Resolution The first alternative is to combine the ... Low-resolution image 1 Projection Low-resolution image 3 High-resolution image Fig. Found inside – Page 124Super-resolution is an algorithm for reconstructing high-resolution image from ... neural network has made much progress in single image super-resolution. Found inside – Page 83Therefore, in tice reconstruction of high-resolution images involves the following tasks: restoration of the low-resolution images, registration of the ... Found inside – Page 637Super resolution imaging technique reconstructs a high-resolution image from a set of low resolution images that are taken from almost the same point of ... This book focuses on the super resolution of images and video. Found inside – Page 294The higher the radiometric resolution, the more accurately the device can capture the ... We will call this a super-resolution image from now on. Found inside – Page 456progress has been made in single image super-resolution [2]. ... The first two methods get higher resolution images from a set of low-resolution input ... Found inside – Page 39Two frequency subbands, LH and HL, were estimated based on wavelet frame in order to get a high-resolution image. The LH and HL frequency subbands were used ... Found inside – Page 132There are three major steps in super-resolution image reconstruction methods ... shifts among images to obtain the high-resolution (alias-free) output. Found inside – Page 46Most of the methods of super-resolution proposed in literature use motion cue for estimating high resolution image. This requires registration of images ... Found inside – Page 557Furthermore, higher-resolution digital scanners are more expensive. Super-resolution algorithms can enable faster scanning at lower resolutions by ... Found inside – Page 48Super Resolution of Quality Images through Sparse Representation A. Bhaskara Rao ... The low resolution image is viewed as down sampled version of a high ... Found inside – Page 26Here, we propose a regularization framework for obtaining super-resolution. Since for natural image super-resolution, we do not have a high resolution image ... Found inside – Page 364Recently, deep CNN has extended its success in high level computer vision to low level computer vision tasks such as color image super-resolution. This book is devoted to the issue of image super-resolution-obtaining high-resolution images from single or multiple low-resolution images. Found inside – Page 286high recurrence data is expelled from low determination picture and ... They are some implicit existing methodologies for the super resolution which ... Found inside – Page 1109We develop an algorithm for the super-resolution optical flow computation by ... Super-resolution is a technique to recover a high-resolution image and/or ... Found inside – Page 211The single image super-resolution that related to our work can be mainly divided ... between low-resolution and high-resolution images from a training set. Found inside – Page 810The key to successfully obtaining high-resolution images is to accurately estimate the registration relationship between viewpoints. Super-resolution ... Found inside – Page 156However, aliasing also contains extra high-frequency information with ... Super-resolution algorithms typically combine multiple aliased images with small ... Found inside – Page 510Super-resolution estimates a high-resolution image from a set of observed low-resolution images of the same scene. We formulate the estimation process as a ... Found inside – Page 835The proposed global linear modal based super-resolution estimates the optimal weights of all the low-resolution training images and a high-resolution image ... Found inside – Page 107This approach is also known as example-based super resolution and generally involves learning correspondences between low- and high-resolution image patches ... Found inside – Page 429Super-resolution processing, which is a method that creates a high-resolution image from multiple low-resolution images, could be an effective solution in ... This book is intended to attract the attention of practitioners and researchers in academia and industry interested in challenging paradigms of image and video coding algorithms with an emphasis on recent technological developments. Found inside – Page 348The single image super-resolution problem is first tackled by some filtering ... a mapping between low- and high-resolution image patches are proposed. Found inside – Page 43Generally, the super resolution algorithm covers image restoration techniques [63, 64] that produce high quality images from noisy, blurred images although ... Found inside – Page 171The application and research of super-resolution image reconstruction can fully exploit ... These super-resolution image reconstruction method has a high ... Found inside – Page 451Image super resolution is the process of obtaining high resolution image from the set of low resolution images. This paper mainly includes interpolation and ... Found inside – Page 270Super-resolution is a technique to recover a high-resolution image from a low resolution image. We develop a variational superresolution method for the ... Found inside – Page 88Image super-resolution is a highly complex task that generates a high-resolution image from a given low-resolution image. It has numerous real-world ... Found inside – Page 6The most common model used is based on observations which are shifted, blurred and decimated (aliased) versions of the high resolution image. Found inside – Page 34111.4 Two pairs of low-resolution and high-resolution SEM images. ... objective of super-resolution is to boost the quality of the low-resolution image to be ... Found inside – Page 152.3.7.1 Hybrid (ML + POCS) Technique In [7], a hybrid algorithm using ML and POCS was proposed for estimating a high-resolution image from multiple blurred, ... Found inside – Page 182Super-resolution is an approach for improving imaging system. Image superresolution is defined as reconstructing a high-resolution image with the details ... Found inside – Page 82The goal is then to obtain a high-resolution image with a higher pixel density than any of the low-resolution images. A typical “zoom factor” is a doubling ... Found inside – Page 215Learning Texture Image Prior for Super Resolution Using Restricted ... because there are many possible high resolution images given a low resolution image. Found inside – Page 627Residual Image Compensations for Enhancement of High-Frequency Components in ... are known as example-based or learning based super-resolution techniques. This book is devoted to the issue of image super-resolution—obtaining high-resolution images from single or multiple low-resolution images. Found inside – Page 274Image resolution gives the information content in the image. Super-resolution involves constructing the high-resolution images from various low-resolution ... Found inside – Page 154when we apply these methods to super-resolve low-resolution images in the real world, because there are no corresponding high-resolution images for training ... Found inside – Page 730Although srcnn has achieved high performance in image super-resolution reconstruction, it still has limitations in the following aspects: (1) it depends on ... Found inside – Page 381They estimate missing high frequency details by interpolating the input low resolution image into a desired scale. The super resolution is performed by the ... The methods of super-resolution proposed in literature use motion cue for estimating high resolution image recurrence data expelled! Found inside – Page 88Image super-resolution is a doubling... found inside – Page 286high data! Page 274Image resolution gives the information content in the image outshine an galaxy. Quality images through Sparse Representation A. Bhaskara Rao SEM images pairs of low-resolution and high-resolution images. 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