An image processing system comprising: a mask associated with a sensor array, said sensor array being capable of capturing an image (110, 112, 114) with a single exposure; said mask having filter portions of several discrete different transparency levels which are spatially pseudo-randomly ordered; wherein each pixel of said sensor array is covered by one mask transparency level; an image reconstruction algorithm; wherein said sensor array communicates with a computer provided with said reconstruction algorithm to reconstruct a plurality of distinct pseudo-random images corresponding to the plurality of several discrete different transparency levels; wherein the plurality of pseudo-random images are each formed by the pixels corresponding to one transparency level, wherein for a single exposure there are several pseudo-random images and the pseudo-random images are modelled by an imaging model represented as x i = f (log( δt i)), where δt i is the exposure time of each pseudo-random image, and f is the camera response function estimated from the acquired pseudo-random images or computed a priori; wherein said image reconstruction algorithm utilizes one of l 1 formulation formulated as follows: l 1 formulation: min ∑ i = 1 n ‖ Ff log δ t i ‖ 1 s u c h t h a t ‖ Pf log δ t i − b ‖ ≤ δ, where n is the number of images to reconstruct; or TV formulation formulated as follows: TV formulation: min ∑ i = 1 n ‖ Ff log δ t i ‖ TV s u c h t h a t ‖ Pf log δ t i − b ‖ ≤ δ where F is an inverse basis transformation, P is a subsampling operator corresponding to the pseudo-random subsampling in pseudo-random image b, and δ is a small chosen number; and wherein said distinct pseudo-random images are combined into a single combined image. a mask associated with a sensor array, said sensor array being capable of capturing an image (110, 112, 114) with a single exposure; said mask having filter portions of several discrete different transparency levels which are spatially pseudo-randomly ordered; wherein each pixel of said sensor array is covered by one mask transparency level; an image reconstruction algorithm; wherein said sensor array communicates with a computer provided with said reconstruction algorithm to reconstruct a plurality of distinct pseudo-random images corresponding to the plurality of several discrete different transparency levels; wherein the plurality of pseudo-random images are each formed by the pixels corresponding to one transparency level, wherein for a single exposure there are several pseudo-random images and the pseudo-random images are modelled by an imaging model represented as x i = f (log( δt i)), where δt i is the exposure time of each pseudo-random image, and f is the camera response function estimated from the acquired pseudo-random images or computed a priori; wherein said image reconstruction algorithm utilizes one of l 1 formulation formulated as follows: l 1 formulation: min ∑ i = 1 n ‖ Ff log δ t i ‖ 1 s u c h t h a t ‖ Pf log δ t i − b ‖ ≤ δ, where n is the number of images to reconstruct; or TV formulation formulated as follows: TV formulation: min ∑ i = 1 n ‖ Ff log δ t i ‖ TV s u c h t h a t ‖ Pf log δ t i − b ‖ ≤ δ where F is an inverse basis transformation, P is a subsampling operator corresponding to the pseudo-random subsampling in pseudo-random image b, and δ is a small chosen number; and wherein said distinct pseudo-random images are combined into a single combined image.