2014/06/22 by Isidora Stanković, Stanković, Isidora
Computer Science · Engineering · #Advanced Data Compression Techniques #Advanced Image Processing Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.48550/arxiv.1407.3695
openalex publication_date 2014/06/22 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
This paper investigates the possibility of reconstruction of images\nconsidering that they are sparse in the DCT transformation domain. Two\napproaches are considered. One when the image is pre-processed in the DCT\ndomain, using 8x8 blocks. The image is made sparse by setting the smallest DCT\ncoefficients to zero. In the other case the original image is considered\nwithout pre-processing, assuming the sparsity as intrinsic property of the\nanalyzed image. A gradient based algorithm is used to recover a large number of\nmissing pixels in the image. The case of a salt-and-paper noise affecting a\nlarge number of pixels is easily reduced to the case of missing pixels and\nconsidered within the same framework. The reconstruction of images affected\nwith salt-and-paper impulsive is compared with the images filtered using a\nmedian filter. The same algorithm can be used considering transformation of the\nwhole image. Reconstructions of black and white and colour images are\nconsidered.\n