%0 Electronic Article %A Afeng Yang %A Xue Jiang %A David Day-Uei Li %K three limited bandwidth constraint %K multiframe blind deconvolution %K Bayesian inference framework %K cost function minimisation %K space object image restoration %K atmospheric turbulence %K iterative recursion %K point spread function %K mixed noise model %X A mixed noise model is proposed and the multi-frame blind deconvolution is used to restore the images of space objects under the Bayesian inference framework. To minimise the cost function, an algorithm based on iterative recursion was proposed. In addition, three limited bandwidth constraints of the point spread functions were imposed into the solution process to avoid converging to local minima. Experimental results show that the proposed algorithm can effectively restore the turbulence degraded images and alleviate the distortion caused by the noise. %@ 0013-5194 %T Multi-frame blind deconvolution of atmospheric turbulence degraded images with mixed noise models %B Electronics Letters %D February 2018 %V 54 %N 4 %P 206-208 %I Institution of Engineering and Technology %U https://digital-library.theiet.org/;jsessionid=1fk9wp6mzqlki.x-iet-live-01content/journals/10.1049/el.2017.4277 %G EN