In delay-intolerant covert communications, supporting high-capacity services (e.g., image or video transmission)

is extremely challenging under stringent covertness constraints and limited bandwidth, due to the fundamental conflict between transmission quality and latency. To address this issue, this paper proposes a novel transmission framework enabled by semantic communication and frequency hopping (FH) for covert wireless communication systems under the finite-blocklength regime. At the transmitter, semantic communication first extracts task-relevant features from the source data to compress the transmitted information, thereby reducing transmission delay while maintaining communication quality. From the receiver’s perspective, the proposed scheme exploits the advantages of FH reception to enhance the signal-to-noise ratio (SNR) at the legitimate receiver, thereby decreasing the decoding error probability and improving transmission efficiency, which in turn

shortens the transmission delay. Specifically, we formulate a biobjective optimization problem that simultaneously maximizes semantic reconstruction quality and minimizes total transmission delay, subject to covertness, average power, and channel equivocation constraints. This non-convex problem is addressed via a hybrid optimization strategy (HOS) that combines outerlayer enumeration with inner-layer alternating optimization (AO) enhanced by the successive convex approximation (SCA) technique. Numerical results demonstrate that the proposed scheme outperforms conventional schemes by achieving lower transmission delay, strong covertness, and effective anti-jamming and anti-interception capabilities.