A computer-implemented image restoration method comprising: acquiring a target image, including acquiring a compound eye vision, CEV, image (402; 1102) of an object, wherein acquiring the CEV image (402; 1102) comprises acquiring the CEV image (402; 1102) based on an intensity of rays received by a plurality of sensing elements (121; 811) through a plurality of lenses (111; 210) provided in an array, and wherein the plurality of lenses (111; 210) are arranged eccentrically with respect to the plurality of sensing elements (121; 811), and generating the target image by rearranging pixels of the CEV image (402; 1102), said rearranging including: determining points of the object that emit a light field, LF, sensed by each of the plurality of sensing elements (121; 811) based on a position relationship between the plurality of sensing elements (121; 811) and rays radiated from points of the object that are spaced apart from an image sensor by a distance greater than a threshold distance; and rearranging pixels corresponding to LF information emitted from points that are adjacent to each other so that the rearranged pixels are adjacent to each other; and restoring an output image (804; 1104) from the acquired target image, based on an image restoration model (850; 1150; 1622) comprising a convolutional layer corresponding to a kernel having a dilation gap, wherein the kernel is a matrix including a plurality of elements and wherein the dilation gap is the gap between non-zero elements within the same row or the same column of the matrix. acquiring a target image, including acquiring a compound eye vision, CEV, image (402; 1102) of an object, wherein acquiring the CEV image (402; 1102) comprises acquiring the CEV image (402; 1102) based on an intensity of rays received by a plurality of sensing elements (121; 811) through a plurality of lenses (111; 210) provided in an array, and wherein the plurality of lenses (111; 210) are arranged eccentrically with respect to the plurality of sensing elements (121; 811), and generating the target image by rearranging pixels of the CEV image (402; 1102), said rearranging including: determining points of the object that emit a light field, LF, sensed by each of the plurality of sensing elements (121; 811) based on a position relationship between the plurality of sensing elements (121; 811) and rays radiated from points of the object that are spaced apart from an image sensor by a distance greater than a threshold distance; and rearranging pixels corresponding to LF information emitted from points that are adjacent to each other so that the rearranged pixels are adjacent to each other; and determining points of the object that emit a light field, LF, sensed by each of the plurality of sensing elements (121; 811) based on a position relationship between the plurality of sensing elements (121; 811) and rays radiated from points of the object that are spaced apart from an image sensor by a distance greater than a threshold distance; and rearranging pixels corresponding to LF information emitted from points that are adjacent to each other so that the rearranged pixels are adjacent to each other; and restoring an output image (804; 1104) from the acquired target image, based on an image restoration model (850; 1150; 1622) comprising a convolutional layer corresponding to a kernel having a dilation gap, wherein the kernel is a matrix including a plurality of elements and wherein the dilation gap is the gap between non-zero elements within the same row or the same column of the matrix.