New digital image interpolation technique

We present a new digital image interpolation technique and analyze its use in digital photography. Our main goal is generate interpolated images with high quality, eliminating or drastically reducing distortions caused by reconstruction error. Our initial hypothesis is that interpolation techniques with frequency response closer to ideal reconstruction can reduce or eliminate reconstruction error, improving image quality. The proposed technique is a new two-dimensional third-order filter, implementing discrete convolution between image samples and interpolation coefficients that are different for each interpolated pixel. To validate the proposed technique, we compared it with piecewise constant, linear and cubic interpolators. We used quality analysis of interpolated images with a new evaluation method and complexity analysis of interpolation algorithms. Based on validation results, we conclude that images interpolated using proposed technique present higher image quality, with significant reduction in reconstruction error, drastically reducing distortions as jagged effect and contrast loss. Thus, our main goal was achieved. One disadvantage is high computational complexity that can be reduced using hardware implementation. The final conclusion is that the proposed image interpolation technique is better than ail other evaluated, can be used as general purpose image interpolation or in reconstruction process used in image display, with many kinds of images, not only with digital photography.