An image gap restoration method is presented based on a combination of a multi-scale pyramid discrete cosine transform (DCT) and edge-guided interpolation of the missing samples. Through a process of pyramid DCT and down-sampling, the image is progressively transformed into a series of reduced size layers until at the apex of the pyramid the gap size is reduced to one sample. The process is then reversed; at each stage, the missing samples are estimated, up-sampled and combined with the available neighbouring samples. The main contributions of this work are the incorporation, within the DCT pyramid layers, of a directional interpolation method using the local edges or textures and a global edge-guided interpolation method based on the Sobel edge detector. Evaluations over a range of images demonstrate that the proposed method results is improved PSNR compared to a range of published works.