Without demosaicing processing, this paper first proposes a new approach to extract more accurate gradient/edge information on mosaic images directly. Next, based on spectral-spatial correlation, a novel adaptive heterogeneity-projection with proper mask size for each pixel is presented. Combining the extracted gradient/edge information and the adaptive heterogeneity-projection values, a new edge-sensing demosaicing algorithm is presented. Based on 24 popular testing images, experimental results demonstrated that our proposed high-quality demosaicing algorithm has the best image quality performance when compared with several recently published algorithms.

Vector quantization (VQ) technique is a well known method in image compression. Employing Winograd's (1968) identity, this article presents a simple improved method in order to cut the computation time in the full search method for VQ nearly 50%. Some experiments are carried out to confirm the theoretical analysis.

A simple vectorized method for calculating a moving sum is developed. Our proposed method is suitable for register-to-register vector computers and entails much less redundant floating-point operations than the vectorized algorithm of Mossberg (1987). We demonstrate the performance of our vectorized algorithm on the CRAY X-MP EA/116se supercomputer.>