In the current era of digital intelligence, the proliferation of sophisticated electromagnetic countermeasures has led to a rise in clutter density inside detection environments. The advancement in radar resolution has led to a shift in target measurement type, transitioning from point targets to extended targets. Both characteristics have emerged as significant contributors to the Information Reduction Factor (IRF) utilised for characterising clutter. In order to address the challenge of detecting extended targets in a strong clutter environment, this study proposes an optimised IRF method and compares its performance with that of the classic IRF method. The experimental results indicate that the Strong Clutter Information Reduction Factor (SCIRF) exhibits limited information and subpar performance in the context of point target measurement, which can be attributed to its relatively small magnitude. On the other hand, the SCIRF associated with extended target measurement demonstrates comparable magnitude and performance to the ideal or weak clutter environment"s IRF under the point target measurement type. Finally, the present study undertakes a theoretical analysis of the underlying rationale for the enhanced performance of SCIRF in the context of the point target measurement type by using local IRF and other indicators, and a plausible explanation for this phenomenon is provided.