Magnification Chromatic Aberration Model Selection

The patent changes the parameters of the mathematical model by offering multiple magnification chromatic aberration models (cubic expression, quadratic expression, and linear expression) with different degrees of freedom. The system selects and switches between these models based on the actual characteristics of the image data and color shift detection results, rather than fixedly using a cubic model. This allows adaptation to different scenarios where detection errors or image structures may make higher-order models inappropriate.

The patent introduces dynamic model selection that adapts to the actual data conditions. Instead of using a fixed cubic model, the system dynamically chooses among cubic, quadratic, and linear models based on evaluation metrics that assess whether the color shift detection data is sufficient and appropriate for each model type. This dynamic adaptation prevents wrong parameter values by selecting simpler models when data is insufficient.

The patent provides multiple models with different mathematical expressions (cubic, quadratic, linear) that have different flexibility characteristics. The system evaluates which model is most appropriate for the actual magnification chromatic aberration characteristics and switches between them. This allows the system to maintain flexibility when cubic approximation is valid while avoiding wrong parameters when the aberration behavior deviates from cubic patterns.

The patent implements a feedback mechanism where the system evaluates the quality and reliability of color shift detection results, then uses this evaluation to select the appropriate magnification chromatic aberration model. The evaluation metric assesses detection accuracy, and based on this feedback, the system chooses among cubic, quadratic, or linear models that are most robust to the detected error levels, thereby improving overall estimation reliability.