Image reconstruction from a reduced set of pixels using a simplified gradient algorithm

A reconstruction of images in the DCT transformation domain based on the adaptive gradient algorithm is considered in this paper. Two approaches are used in the reconstruction. In the first approach, the image is pre-processed using 8×8 blocks, such that the smallest DCT coefficients are set to zero in order to make the image sparse. The second approach reconstructs the image without the pre-processing step. It has been assumed that the sparsity is an intrinsic property of the analyzed image. An adaptive gradient based algorithm is used to recover a large number of missing pixels in the image. In order to improve the calculation complexity, in this paper we propose an improved version of recently proposed adaptive gradient algorithm, which is now reduced to a single, automatically determined parameter. The previous reconstruction of black and white and colour images is repeated with a significant calculation efficiency improvement.