The Region of Interest (ROI) Image reconstruction methods based on feature and color would be useful for the non-contact detection of defects in composite, metallic, and hybrid composite/metallic structures. An improved adaptive method of processing image data in multi-objective optimization has been developed to enable automated, real-time reconstruction of possibly engineering design, parameter estimation, and image reconstruction. There are three approaches for this purpose: Firstly, ROI with a gradient-based method improve quality enhancements and moderate convergence efficiency, and continue to develop the gradient evaluations “smart” imager cells method for image reconstruction. Secondly, the multi-objective framework will integrate the analysis image reconstruction for feature and color, instead of relying on one image codes to perform the analysis for all disciplines, and develop artificial intelligence algorithms for image classification based on the “smart” imager cells approach for simplifying multi-objective optimization. Lastly, the ROI model develop artificial intelligence algorithms for image classification based on the “smart” imager cells approach for simplifying multi-objective optimization, implementation of image reconstruction to optimize the ROI model in which lieu to the computationally expensive functions.
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