Image sensors are integral components of many critical intelligent systems. However, a growing threat, known as Electromagnetic Signal Injection Attacks (ESIA), poses a significant risk to these systems. ESIA enables attackers to remotely manipulate images captured by cameras which can potentially lead to malicious actions and catastrophic consequences. Despite the severity of this threat, the effects of ESIA remain poorly understood, and effective countermeasures are lacking. This paper aims to address these gaps by investigating ESIA from two distinct aspects: pixel loss and color strips. By analyzing these aspects separately on image classification tasks, we gain a deeper understanding of how ESIA can compromise intelligent systems. Additionally, we explore a lightweight solution to mitigate the effects of ESIA. Our findings provide valuable insights for future research and development in the field of camera security and intelligent systems.