Volume : III, Issue : XII, December - 2014

Optimum Threshold Decision in Super Resolution using DCT with Local Ternary Pattern Operator

Kiran P. Patel

Abstract :

 In this paper, I present  what should be an ideal value of threshold while reconstructing HR image . I use a  new learning based technique to super–resolve a low resolution image using “Local Ternary Pattern Operator” and a database of low resolution (LR) images and corresponding high resolution (HR) versions. The local geometry of an image is conveyed by image features such as edges, corners and curves. We encode these features with local ternary pattern operator. The missing high resolution features of the low resolution observation are learnt in the form of discrete cosine transform coefficients from high resolution images in the training database. Experiments are conducted on real world natural images and results are compared with  taking different sizes of database of low resolution (LR) images and corresponding high resolution (HR) versions. The results help us in deciding the best threshold value to achieve good quality HR image.

Keywords :

Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Kiran P.Patel, Optimum Threshold Decision in Super Resolution using DCT with Local Ternary Pattern Operator, International Journal of Scientific Research, Vol : 3, Issue : 12 December 2014

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