Study On Electronic Digital Image Stabilization Technology For The Image Sequences Of MAV

Electronic Digital Image Stabilization (EDIS) has become the future trend ofdevelopment, because of its advantages of good Integration, low energyconsumption, simple control complexity, and high image stabilizing precision,reasonable price, wide range of applications, flexible and portable. This thesis,supported by the directional project with knowledge innovation and importantengineering of Chinese Academy of Sciences, has put forward the effective methodfor realizing stabilization of jitter image sequences. Intensive study of the techniqueof electronic image stabilization of MAV has been carried out.This thesis elaborated the fundamental principle and main processes of EDIS,especially for the key steps (motion estimation) adopted by overseas electronicimage stabilization system. On this basis, combining with MAV's characteristics andairborne environment, airborne jitter of image sequence were processed by twosolutions which based on homography with sift algorithm and Fuzzy neural networkrespectively. At the end of the relevant sections, two solutions were verified throughthe actual experiment and the simulation of the system.The first solution analyzed the reason why the traditional image motion modelwasn't suitable for MAV, put forward and deduced the image motion modelaccording to homography perspective projection principle. In the local motion estimation step, SIFT operator was verified that certain geometric deformable, scenecomplexity of higher image local characteristics can be accurately match, and get ridof small moving objects as a feature location.The second would focus on motion prediction. The traditional EDIS based onmotion estimation after the shooting, that is to say, to calculate the image sequencesbetween adjoining frames of the relative displacement, and then implementation ofcompensation. Since this article airborne imaging equipment jitter was caused bywind and its own motor, and therefore, the jitter has certain regularity. This solutionusing fuzzy neural network function approximation and learning ability to simulatethe jitter law predicted the location of jitter airborne imaging equipment in the nextmoment and then, compensated the difference.In accordance with the system requirements it has been designed that ahigh-performance embedded image stabilization system based on ARM and FPGA.For the purpose of evaluation, we propose several performance measures to describethe fidelity, speed, and range of displacements supported by such systems. Thesemeasures can also be used as development tools to determine the influence of certainmodules in the overall performance of a system.