Hexagonal image structure represents an image as a collection of hexagonal pixels rather than square pixels in the traditional image structure. However, all the existing hardware for capturing image and for displaying image are produced based on square pixel image structure. Therefore, it becomes important to find a proper software approach to mimic the hexagonal structure so that images repres...

This paper presents the nearest neighbor value (NNV) algorithm for high resolution (H.R.) image interpolation. The difference between the proposed algorithm and conventional nearest neighbor algorithm is that the concept applied, to estimate the missing pixel value, is guided by the nearest value rather than the distance. In other words, the proposed concept selects one pixel, among four direct...

This work presents a new method of fast cubic and higher order image interpolation. The evaluation of the piecewise n-th order polynomial kernels is accelerated by transforming the polynomials into the interval [0, 1], which has the advantage that some terms of the polynomials disappear, and that several coefficients could be precalculated, which is proven in the paper. The results are exactly ...

Uniformly sampled images are often used to interpolate other data acquired more sparsely with an entirely different mode of measurement. For example, downhole tools enable geophysical properties to be measured with high precision near boreholes that are scattered spatially, and less precise seismic images acquired at the earth’s surface are used to interpolate those properties at locations far ...

Uniformly sampled images are often used to interpolate other data acquired more sparsely with an entirely different mode of measurement. For example, downhole tools enable geophysical properties to be measured with high precision near boreholes that are scattered spatially, and less precise seismic images acquired at the earth’s surface are used to interpolate those properties at locations far ...

Interpolation technique in color image demosaicing is a big challenge to obtain RGB channels as perceived by humans. The existing demosaicing methods adopt i terative residual interpolation (IRI) technique, which performs iterations on the residuals. These methods are unable to reconstruct G channel efficiently with less iterations. Hence a new demosaicing method is proposed, which performs les...

We establish a link between classical osculatory interpolation and modern convolution-based interpolation and use it to show that two well-known cubic convolution schemes are formally equivalent to two osculatory interpolation schemes proposed in the actuarial literature about a century ago. We also discuss computational differences and give examples of other cubic interpolation schemes not pre...

Application of geometric transformation to images requires an interpolation step. When applied to image rotation, the presently most e cient GPU implementation for the cubic spline image interpolation still cost about 10 times as much as linear interpolation. This implementation involves two steps: a pre lter step performs a two-pass forward-backward recursive lter, then a cubic polynomial inte...

Suppose we want to digitally enlarge a photograph. The input is a single, low-resolution image, and the desired output is an estimate of the high-resolution version of that image. This problem can be phrased as one of “image interpolation”: we seek to interpolate the pixel values between our observed samples. Image interpolation is sometimes called super-resolution, since we are estimating data...

Radial Basis Functions (RBF) interpolation theory is briefly introduced at the “application level” including some basic principles and computational issues. The RBF interpolation is convenient for un-ordered data sets in n-dimensional space, in general. This approach is convenient especially for a higher dimension N 2 conversion to ordered data set, e.g. using tessellation, is computationally v...