Image reconstruction method for inhibiting industrial imaging ladder artifacts

Abstract

The invention discloses an image reconstruction method for inhibiting industrial imaging ladder artifacts, which is characterized in that a conductivity distribution coefficient is processed by combining a novel processing function, and finally, an operator for reconstructing conductivity distribution is used for reconstructing an optimal conductivity distribution coefficient to obtain optimal conductivity distribution. The sparse regular term can restore the most real solution by using less data, an unconstrained problem in the optimization model is converted into a corresponding constrained problem, the sub-problems are iteratively solved, iteration can be ended until the specified number of iterations is met, and the optimal conductivity distribution coefficient at the moment is obtained. And finally, the optimal conductivity distribution is obtained by using the operator for reconstructing the conductivity distribution, and imaging is carried out. Step artifacts in the background of the image reconstructed by the TV regularization method are effectively reduced, the quality of the reconstructed image is improved, relatively good noise immunity is achieved, and new possibility is provided for the field of industrial imaging.

Description

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AI Technical Summary

Benefits of technology

This patented technology helps prevent images from being reconstructed with errors due to variations during production or processing steps. It uses specific techniques that help reduce these issues while still maintaining high-quality results for subsequent use.

Problems solved by technology

This patented describes different methods that aim at improving the accuracy and resolution of electric tomographic scans by reducing unwanted noise caused during data acquisition or reconstructions. One approach involves adding extra materials called dielectic layers into the structure being analyzed through measurements made between multiple pairs of sensors placed close together. These techniques help prevent distortion errors associated with traditional methods like resistive tomography. Another technique proposed uses specific mathematical relationships involving certain physical properties to enhance image formation. By combining these techniques, it becomes possible to achieve improved results without compromising their effectiveness over conventional methods.

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