| Abstrakt: |
In this paper, we present a novel approach for adaptive and progressive image acquisition, based on the progressive transmission of an image decomposed into compositions and superpositions of monovariate functions. The monovariate functions are iteratively constructed from the acquired data, to progressively reconstruct the final image: the transmission is performed directly in the 1D space of the monovariate functions, independently of any statistical properties of the image. Each monovariate function contains only a fraction of the pixels of the image. Each new transmitted monovariate function adds data to the previously transmitted monovariate functions. After each partial acquisition, by using the updated monovariate functions, the image is reconstructed with an increased resolution. Finally, once all the monovariate functions have been transmitted, the original image is reconstructed exactly at the maximum resolution of the sensor. This approach is characterized by its flexibility: any numbers of intermediate transmissions and reconstructions are possible. Moreover, the intermediate images can be reconstructed at any resolution, and for any number of intermediate reconstructions, the original image will be exactly reconstructed. Finally, the quantity of data is independent of the number and resolutions of intermediate reconstructions. Our contributions include the application of a flexible progressive transmission scheme to provide a progressive and flexible acquisition at various resolutions. Moreover, the accuracy of the full resolution image is preserved, and the acquired data are encrypted and resilient to packet-loss. |
