Abstract: A system and method of removing turbulence from an image of a time ordered sequence of image frames. The method comprises removing effects of turbulence from a first image of the sequence to create an initial corrected image frame; determining a number of iterations required to achieve a desired turbulence removal for a subsequent image in the sequence and satisfy a latency constraint and an available memory capacity; and determining, based on the number of required iterations, a minimum set of image frames required to remove turbulence from the subsequent image. The minimum set of image frames comprises: a number of image frames of the sequence, a number of image frames generated in an intermediate iteration of turbulence removal and the initial corrected image frame. The method further comprises using the minimum set of image frames to remove turbulence from the subsequent image of the sequence.

Abstract: A system and method of removing turbulence from an image of a time ordered sequence of image frames. The method comprises removing effects of turbulence from a first image of the sequence to create an initial corrected image frame; determining a number of iterations required to achieve a desired turbulence removal for a subsequent image in the sequence and satisfy a latency constraint and an available memory capacity; and determining, based on the number of required iterations, a minimum set of image frames required to remove turbulence from the subsequent image. The minimum set of image frames comprises: a number of image frames of the sequence, a number of image frames generated in an intermediate iteration of turbulence removal and the initial corrected image frame. The method further comprises using the minimum set of image frames to remove turbulence from the subsequent image of the sequence.

Abstract: Methods, apparatus, and computer readable media are provided for image compression. Edge elements of an image comprising pixels are established by analyzing pixel values associated with the pixels of the image. The edge elements are organized in an edge data structure having at least two dimensions. The edge data structure is compacted along a first dimension by arranging the established edge elements adjacent to each other along the first dimension in a compacted edge data structure. Compressed edges in a second dimension in the compacted edge data structure are determined by: determining edge elements to be joined along a second dimension in the compacted edge data structure based on pixel values of neighboring edge elements, along the second dimension, in the compacted edge data structure; and compressing the image by encoding formed edges, the edges being formed by joining the determined edge elements.

Abstract: Methods, apparatus, and computer readable media are provided for image compression. Edge elements of an image comprising pixels are established by analysing pixel values associated with the pixels of the image. The edge elements are organised in an edge data structure having at least two dimensions. The edge data structure is compacted along a first dimension by arranging the established edge elements adjacent to each other along the first dimension in a compacted edge data structure. Compressed edges in a second dimension in the compacted edge data structure are determined by: determining edge elements to be joined along a second dimension in the compacted edge data structure based on pixel values of neighbouring edge elements, along the second dimension, in the compacted edge data structure; and compressing the image by encoding formed edges, the edges being formed by joining the determined edge elements.