Volume 8 Issue 1 - January 2017

  • 1. Image super resolution using sparse neighbor embedding and clustering algorithm

    Authors : Dr.dharmanna L, Deekshith K

    Pages : 616-621

    DOI : http://dx.doi.org/10.21172/1.81.081

    Keywords : Super Resolution, Sparse neighbor embedding, histograms of oriented gradients, K-Means clusters, K-NN Classification

    Abstract :

    This paper presents a new approach to image super resolution, based upon Sparse Neighbor Embedding and clustering algorithm .Consider a low resolution image as input. Then do LR patch separation, followed by feature extraction using histograms of oriented gradients (HOG). Then perform classification using K-means clustering algorithm. Then perform Sparse Neighbor Embedding. Finally synthesize HR patches and subject it to de-blurring algorithm to obtain a Super-Resolution Image.

    Citing this Journal Article :

    Dr.dharmanna L, Deekshith K, "Image super resolution using sparse neighbor embedding and clustering algorithm", https://www.ijltet.org/journal_details.php?id=910&j_id=3641, Volume 8 Issue 1 - January 2017, 616-621, #ijltetorg