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Optical Engineering

Modified cubic convolution scaler with minimum loss of information
Author(s): Jong-Ki Han; Hyung-Myung Kim
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Paper Abstract

The authors derive an adaptive version of cubic convolution interpolation for the enlargement or reduction of digital images by arbitrary scaling factors. The adaptation is performed in each subblock (typically LxL rectangular) of an image. It consists of three phases: two scaling procedures (i.e., forward and backward interpolation) and an optimization of the interpolation kernel. In the forward interpolation phase, from the sampled data with the original resolution, we generate scaled data with different (higher or lower) resolution. The backward interpolation produces new discrete data by applying another interpolation to the scaled one. The phases are based on a cubic convolution interpolation whose kernel is modified to adapt to local properties of the data. During the optimization phase, we modify the parameter values to decrease the disparity between the original data and those resulting from another interpolation on the different-resolution output of the forward interpolating phase. The overall process is repeated iteratively. We show experimental results that demonstrate the effectiveness of the proposed interpolation method. The algorithm exhibits significant improvement in the minimization of information loss when compared with the conventional interpolation algorithms.

Paper Details

Date Published: 1 April 2001
PDF: 7 pages
Opt. Eng. 40(4) doi: 10.1117/1.1355250
Published in: Optical Engineering Volume 40, Issue 4
Show Author Affiliations
Jong-Ki Han, Korea Advanced Institute of Science and Technology (South Korea)
Hyung-Myung Kim, Korea Advanced Institute of Science and Technology (South Korea)


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