Disclosed is a swatch sparsity image
inpainting method with directional factors combined. The swatch sparsity image
inpainting method mainly comprises the steps of conducing preprocessing on an image to be inpainted by the utilization of an existing image
inpainting algorithm, extracting directional factors in four directions from the preprocessed image through non-subsampled
contourlet transform, determining a new structural sparseness function and a new matching criterion according to the color-directional factor weighting distance, determining a filling-in order by means of the structure sparseness function and searching for a plurality of matching blocks according to the new matching criterion, establishing a constraint equation with
color space local
sequential consistency and directional factor local
sequential consistency, optimizing and solving the constraint equation to obtain sparse representation information of the matching blocks, conducting filling, and updating filled-in regions until damaged areas are completely filled in. By means of the swatch sparsity image inpainting method, the consistency of the structure part, the clearness of the texture part and the
sequential consistency of neighborhood information can be effectively kept, and the swatch sparsity image inpainting method is particularly applicable to inpainting of real pictures or composite images with complex textures and complex structural characteristics.