A new efficient method for interpolation and decimation of images by arbitrary ratio using block transform coefficients such as discrete cosine transform (DCT) is obtained. Due to multiple standards in image/video coding schemes, it is expected that decoders as well as display or recording devices need to convert the received signal from one format to another. It is essential that high quality resampling be done in lowest hardware complexity since such processing normally requires a large amount of computations. In this paper, a block based non-integer ratio resampling algorithm is developed which can be implemented very efficiently without significant increase of system complexity. For the implementation of the proposed approach, an inverse block transform (for example, inverse DCT) and resampling process are combined into one process so that no additional processing stage is required. The proposed approach called truncated overlap-add with compensation (TOAC) technique provides cost effective solution to resampling problems. It can be implemented on a single VLSI chip together with inverse block transform operations.

An approach to obtaining high-resolution image reconstruction from low-resolution, blurred, and noisy multiple-input frames is presented. A recursive-least-squares approach with iterative regularization is developed in the discrete Fourier transform (DFT) domain. When the input frames are processed recursively, the reconstruction does not converge in general due to the measurement noise and ill-conditioned nature of the deblurring. Through the iterative update of the regularization function and the proper choice of the regularization parameter, good high-resolution reconstructions of low-resolution, blurred, and noisy input frames are obtained. The proposed algorithm minimizes the computational requirements and provides a parallel computation structure since the reconstruction is done independently for each DFT element. Computer simulations demonstrate the performance of the algorithm.

An approach to high-resolution image reconstruction from blurred noisy multiframes is presented. A recursive least square estimation with regularization method is applied for high resolution estimation. This approach provides a unified algorithm for deblurring, noise removal, and high resolution reconstruction. Due to the recursive nature of the algorithm, computations are minimized. The algorithm is highly parallel since reconstruction is done independently for each pel in the transform domain. Computer simulations demonstrate the performance of the algorithm.>