Abstract
Spline functions due to their smoothing and interpolating properties are gaining popularity in engineering applications and image processing. In reality, the discretized image is a representation of the average-image intensity or photographic density over a certain area. To reduce the channel or storage requirements, the reduction in the number of pixels may be an alternative, consequently the missing details may be obtained by interpolation.In the present paper, the interpolation techniques by the spline functions of odd degree are developed and used on an exponential function and an image data, to reconstruct the original function. Results show that a good data-reduction ratio can be obtained with reasonable mean-square error in reconstruction. The technique of interpolation is applied to an image. The results shown are quite encouraging.
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