Open AccessA Sub-Dictionary Approach for Image Super Resolution Based on Sparse Representation
Author(s) -
Ganesh Venkatesh,
K. E. Sreenivasa Murthy
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.20.14776
Subject(s) - representation (politics) , computer science , coding (social sciences) , word (group theory) , image (mathematics) , algorithm , code (set theory) , association (psychology) , resolution (logic) , artificial intelligence , sparse approximation , quality (philosophy) , theoretical computer science , arithmetic , natural language processing , computer vision , mathematics , psychology , statistics , law , geometry , set (abstract data type) , politics , political science , psychotherapist , programming language , philosophy , epistemology
In this paper we attempt to speak to a novel way to deal with single-picture super-determination, established on inadequate flag representation. Investigation on picture estimations prescribes that picture covers can be very much portrayed as a scanty straight amalgamation of basics from a reasonably favored over entire word reference. Roused by this examination, we seek after a meager show for each fix of the low-determination input, and earlier utilize the estimations of this exhibit to induce the high-determination profitability. Theoretic results from compacted recognizing prescribe that under gentle conditions, the meager show can be fittingly enhanced from the down tested signals.We utilize nearby sub-word references to adaptively code picture covers, which can represent picture neighborhood gatherings improved and affirm the sparsity belonging of the picture. Moreover, we rehearse portion weakening to describe HR and LR coding amounts to internment and guide the crucial non-direct association among them. Such speaking to is of focal noticeable quality in the picture SR risky, for the reason that high-arrange estimations assume a considerable part in the modifying of the detail setup of a HR picture.