A Non-Negativity Iterative Approach to Image Deconvolution for SKA

We introduce a novel algorithm for image deconvolution applicable to interferometric radio observations, based on the assumption of non-negative source fluxes. The method enables rapid and efficient image reconstruction in an iterative manner, without requiring prior knowledge or training. Its computational cost scales linearly with the number of pixels: for example, a $512\times 512$ image can be processed in about 1-2 seconds on a standard laptop. We validate the algorithm using both point sources and an extended galaxy image, incorporating a realistic SKA-Low PSF with incomplete $uv$-coverage, though tests are conducted in noise-free simulations. Comparison with the CLEAN method demonstrates that our approach yields a good reconstruction, showing particular promise for the SKA and VLBI observations with sparse $uv$-coverage.