Since the transmission of the uncompressed image in the context of wireless visual sensor networks (WVSNs) consumes less energy than transmitting the compressed image, developing energy-aware compression algorithms are mandatory to extend the camera node's lifetime and thereby the whole network lifetime. The present paper studies a low-complexity image compression algorithm in the context of WVSNs. This algorithm consists of applying a pruning approach on a DCT approximation transform. The scheme is investigated in terms of computation cycles, processing time, energy consumption and image quality. Experimental works are conducted using the Atmel Atmega128 processor of Mica2 and MicaZ sensor boards. Simulation results show that the studied scheme can exhibit a competitive performance when compared against other algorithms. Furthermore, the scheme can achieve the best tradeoff between energy consumption and image quality.