Example Based Single Frame Image Super Resolution By Support Vector Regression

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Example Based Single-frame Image Super-resolution by ...

    http://www.hpl.hp.com/techreports/2010/HPL-2010-157.pdf
    Example Based Single-frame Image Super-resolution by Support Vector Regression problem. A commonly used constrain is the smoothness of an image. In multiple frames super-resolution, more constraints are given, but the nature of problem is still ill-posed since there are different models which lead to different solutions.

Example Based Single-Frame Image Super-Resolution by ...

    https://www.researchgate.net/publication/228624667_Example_Based_Single-Frame_Image_Super-Resolution_by_Support_Vector_Regression
    Recently, Dalong Li and Steven Simske [3], reported their work based on an example based single-frame image super resolution using support vector regression (SVR). Experimental results indicate ...

Example Based Single-frame Image Super-resolution by ...

    http://www.hpl.hp.com/techreports/2010/HPL-2010-157.html
    Keyword(s): Support Vector Regression, single-frame image super- resolution, ill-posed problem, example-based, machine learning Abstract: As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in …

Example Based Single-Frame Image Super-Resolution by ...

    http://www.jprr.org/index.php/jprr/article/view/253
    Example Based Single-Frame Image Super-Resolution by Support Vector Regression. Full Text . Close . ... As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in the context of machine learning. However, the proposed method in this paper is different from other learning based ...

Improved Image Super-Resolution by Support Vector …

    http://vislab.ucr.edu/PUBLICATIONS/pubs/Journal%20and%20Conference%20Papers/after10-1-1997/Conference/2011/Improved%20Image%20Super-Resolution%20by%20Support%2011.pdf
    for image SR [4] [5] [6]. In [4] an example based learning algorithm is proposed by predicting the HR images from LR images via a Markov Random Field (MRF) model that is computed by belief propagation. In [5] support vector regression (SVR) is applied to single image super-resolution in Discrete Cosine Transform (DCT) domain.

Example Based Single-frame Image Super-resolution by ...

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.225.5314
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Support Vector Regression, single-frame image super-resolution, ill-posed problem, example-based, machine learning As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in the context of machine learning.

SK-SVR: Sigmoid kernel support vector regression based in ...

    https://www.sciencedirect.com/science/article/pii/S0167865517301241
    A new in-scale single image super-resolution approach is proposed in this paper. The proposed approach effectively applies support vector regression (SVR) for learning and generates high resolution image.Cited by: 7

Interpolation Based Image Super Resolution by Support ...

    http://www.ijcsit.com/docs/Volume%205/vol5issue04/ijcsit2014050439.pdf
    Interpolation Based Image Super Resolution by Support-Vector-Regression Sowmya. M 1, Anand M.J 2 1Final Year M.Tech Student, Department Of Electronics And Communication, PES College Of Engineering, Mandya, Karnataka, India. 2Assistant Professor, Department Of Electronics And Communication, PES College Of Engineering, Mandya, Karnataka, India. ...

Example Based Single-frame Image Super-resolution by ...

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.730.9629
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): As many other inverse problems, single-frame image super-resolution is an ill-posed prob-lem. The problem has been approached in the context of machine learning. However, the proposed method in this paper is different from other learning based methods regarding how the input/output are formulated as well as how the ...

(PDF) Single Image Superresolution Based on Support Vector ...

    https://www.researchgate.net/publication/224641292_Single_Image_Superresolution_Based_on_Support_Vector_Regression
    In this paper, a novel super-resolution face reconstruction framework based on support vector regression (SVR) about a single image is presented. Given some input data, SVR can precisely predict ...

Example Based Single-Frame Image Super-Resolution by ...

    https://www.researchgate.net/publication/228624667_Example_Based_Single-Frame_Image_Super-Resolution_by_Support_Vector_Regression
    Recently, Dalong Li and Steven Simske [3], reported their work based on an example based single-frame image super resolution using support vector regression (SVR). Experimental results indicate ...

Example Based Single-frame Image Super-resolution by ...

    http://www.hpl.hp.com/techreports/2010/HPL-2010-157.pdf
    Example Based Single-frame Image Super-resolution by Support Vector Regression problem. A commonly used constrain is the smoothness of an image. In multiple frames super-resolution, more constraints are given, but the nature of problem is still ill-posed since there are different models which lead to different solutions.

Example Based Single-frame Image Super-resolution by ...

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.225.5314
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Support Vector Regression, single-frame image super-resolution, ill-posed problem, example-based, machine learning As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in the context of machine learning.

Example Based Single-frame Image Super-resolution by ...

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.730.9629
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): As many other inverse problems, single-frame image super-resolution is an ill-posed prob-lem. The problem has been approached in the context of machine learning. However, the proposed method in this paper is different from other learning based methods regarding how the input/output are formulated as well as how the ...

Example Based Single-frame Image Super-resolution by ...

    http://www.hpl.hp.com/techreports/2010/HPL-2010-157.html
    Keyword(s): Support Vector Regression, single-frame image super- resolution, ill-posed problem, example-based, machine learning Abstract: As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in the context of machine learning.

Example Based Single-Frame Image Super-Resolution by ...

    http://www.jprr.org/index.php/jprr/article/viewFile/253/67
    As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in the context of machine learning. However, the proposed method in this paper is different from other learning based methods regarding how the input/output are formulated as well as how the learning is done.

SK-SVR: Sigmoid kernel support vector regression based in ...

    https://www.sciencedirect.com/science/article/pii/S0167865517301241
    A new in-scale single image super-resolution approach is proposed in this paper. The proposed approach effectively applies support vector regression (SVR) for learning and generates high resolution image.Cited by: 7

Improved Image Super-Resolution by Support Vector …

    http://vislab.ucr.edu/PUBLICATIONS/pubs/Journal%20and%20Conference%20Papers/after10-1-1997/Conference/2011/Improved%20Image%20Super-Resolution%20by%20Support%2011.pdf
    for image SR [4] [5] [6]. In [4] an example based learning algorithm is proposed by predicting the HR images from LR images via a Markov Random Field (MRF) model that is computed by belief propagation. In [5] support vector regression (SVR) is applied to single image super-resolution in Discrete Cosine Transform (DCT) domain.

Image Superresolution Using Support Vector Regression ...

    https://www.researchgate.net/publication/6289713_Image_Superresolution_Using_Support_Vector_Regression
    In this paper, a novel super-resolution face reconstruction framework based on support vector regression (SVR) about a single image is presented. Given some input data, SVR can precisely predict ...

Interpolation Based Image Super Resolution by Support ...

    http://www.ijcsit.com/docs/Volume%205/vol5issue04/ijcsit2014050439.pdf
    Interpolation Based Image Super Resolution by Support-Vector-Regression Sowmya. M 1, Anand M.J 2 1Final Year M.Tech Student, Department Of Electronics And Communication, PES College Of Engineering, Mandya, Karnataka, India. 2Assistant Professor, Department Of Electronics And Communication, PES College Of Engineering, Mandya, Karnataka, India. ...

Feature dimensionality reduction for example-based image ...

    http://www.hpl.hp.com/techreports/2011/HPL-2011-56.pdf
    Support Vector Regression, single-frame image super-resolution, PSNR, PCA Support vector regression has been proposed in a number of image processing tasks including blind image deconvolution, image denoising and single frame super-resolution. As for other machine learning methods, the training is slow.

Example Based Single-frame Image Super-resolution ... - CORE

    http://core.ac.uk/display/21833202
    Support Vector Regression, single-frame image super-resolution, ill-posed problem, example-based, machine learning As many other inverse problems, single-frame image super-resolution is an ill-posed problem. The problem has been approached in the context of machine learning.

Satellite Super Resolution Image Reconstruction Based on ...

    https://link.springer.com/chapter/10.1007%2F978-3-319-13461-1_22
    Li, D., Simske, S.: Example Based Single-frame Image Super-resolution by Support Vector Regression. Journal of Pattern Recognition Research 1, 104–118 (2010) CrossRef Google Scholar 11.

Example Based Single-frame Image Super-resolution by ...

    http://www.docin.com/p-1464248686.html
    Since example based approaches whichwe know exactly what outputshall objectivelymeasure performancesince trainedmodel “correctly”restore imagerather than image,e.g. sharpening. Keywords: Support Vector Regression, single-frame image super-resolution, ill-posed problem, example-based, machine learning.

Image super-resolution using multi-layer support vector ...

    https://www.researchgate.net/publication/271456345_Image_super-resolution_using_multi-layer_support_vector_regression
    Existing support vector regression (SVR) based image superresolution (SR) methods always utilize single layer SVR model to reconstruct source image, which are incapable of restoring the details ...

Single Image Superresolution Based on Support Vector ...

    https://www.infona.pl/resource/bwmeta1.element.ieee-art-000001660414
    Support vector machine (SVM) regression is considered for a statistical method of single frame superresolution in both the spatial and discrete cosine transform (DCT) domains. As opposed to current classification techniques, regression allows considerably more freedom in the determination of missing high-resolution information.

Single Image Super-Resolution Using Deep Learning - MATLAB ...

    https://www.mathworks.com/help/images/single-image-super-resolution-using-deep-learning.html
    Introduction. Super-resolution is the process of creating high-resolution images from low-resolution images. This example considers single image super-resolution (SISR), where the goal is to recover one high-resolution image from one low-resolution image.

SINGLE FRAME IMAGE SUPER RESOLUTION USING …

    https://arxiv.org/pdf/1011.2272
    probabilistic framework. In [30] Kwang In Kim et al proposed a regression-based method for single imag super-resolution. Kernel ridge regression (KRR) was used to estimate the high-frequency details of the underlying high-resolution image. Joshy and Choudhari have proposed a learning based method for image super resolution from zoomed observations.

Fast single image super-resolution using sparse Gaussian ...

    https://www.sciencedirect.com/science/article/pii/S0165168416302973
    Gaussian process (GP) regression is a popular statistical kernel method for learning the relationship hidden in data. However, the extensive calculation of kernel matrix hinders the further applications in many computer vision tasks such as super-resolution (SR).

Super-Resolution via Deep Learning - GroundAI

    https://www.groundai.com/project/super-resolution-via-deep-learning/1
    In this paper we attempt to survey the deep learning literature in the context multimedia super-resolution. The main focus is on three areas, viz. still images, videos and higher dimensions, especially the range data. For each of the three, we first introduce the relevant benchmarks before reviewing the contemporary literature on deep learning based super-resolution, which is followed by a ...

A cockpit of multiple measures for assessing film ...

    https://www.sciencedirect.com/science/article/pii/S0167865520300076
    A notable example of such approaches is presented in , where seventeen IQ measures are merged through a support vector regression model , trained on a set of images automatically generated and labelled. Though interesting, this approach has one main weakness due to the fact that the user is provided with a unique quality measure and the ...

Temporally Coherent GANs for Video Super-Resolution (TecoGAN)

    https://www.groundai.com/project/temporally-coherent-gans-for-video-super-resolution-tecogan/1
    Super-resolution for natural images is a classic and difficult problem in the field of image and video processing. For single image super-resolution (SISR), deep learning based methods achieve state-of-the-art peak signal-to-noise ratios (PSNR), while architectures based on Generative Adversarial Networks (GANs) achieve major improvements in terms of perceptual quality.

Wavelet denoising of multiframe optical coherence ...

    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296543/
    Mar 01, 2012 · We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and structure estimation.

Multi-Frame Super-Resolution Medical Imaging ...

    https://arxiv.org/pdf/1812.09375
    (a) Low-resolution frames (b) Super-resolved image Figure 1.2: Example of multi-frame super-resolution by exploiting subpixel motion across a set of low-resolution frames.(a)Sequence of low-resolution frames.(b)Super-resolved image (4 magnification) gained from 17 frames using the method proposed in Chapter4. for the overall optical resolution.



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