Image Superresolution Using Support Vector Regression

  title={Image Superresolution Using Support Vector Regression},
  author={Karl S. Ni and Truong Q. Nguyen},
  journal={IEEE Transactions on Image Processing},
A thorough investigation of the application of support vector regression (SVR) to the superresolution problem is conducted through various frameworks. Prior to the study, the SVR problem is enhanced by finding the optimal kernel. This is done by formulating the kernel learning problem in SVR form as a convex optimization problem, specifically a semi-definite programming (SDP) problem. An additional constraint is added to reduce the SDP to a quadratically constrained quadratic programming (QCQP… CONTINUE READING
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