The demand for high-resolution images is gradually increasing, whereas many imaging systems have been designed to enable a certain level of aliasing during image acquisition. In this sense, digital image processing approaches have recently been investigated to reconstruct a high-resolution image from aliased low-resolution images. However, since the subpixel motion information is assumed to be accurate in most conventional approaches, the satisfactory high-resolution image cannot be obtained when the subpixel motion information is inaccurate. Hence, we propose a new algorithm to reduce the distortion in the reconstructed high-resolution image due to the inaccuracy of subpixel motion information. For this purpose, we analyze the effect of inaccurate subpixel motion information on a high-resolution image reconstruction, and model it as zero-mean additive Gaussian errors added respectively to each low-resolution image. To reduce the distortion, we apply the modified multichannel image deconvolution approach to the problem. The validity of the proposed algorithm is demonstrated both theoretically and experimentally.
Bibliographical noteFunding Information:
This work was supported in part by the Brain Korea 21 sponsorship program.
All Science Journal Classification (ASJC) codes
- Atomic and Molecular Physics, and Optics