Most existing works on compressive imaging require electronic devices to perform the spatial optical modulation (SOM) or sparsifying transform (ST), which increase the cost and power consumption in field application. For the implementation of compressive imaging with a cheaper cost, the sensing strategy with blocking random pulse sampling (BRPS) is proposed. Instead of using the SOM and ST required by conventional technologies, the BRPS sampling can be achieved by the random unit-pulse in spatial domains. For actual application, the BRPS can be realized by address controlling for CMOS image sensors with a low resolution. For BRPS sampling, the image can be reconstructed by TVAL3. Experimental results show that, the BRPS achieves better reconstruction than conventional compressive sensing with Gaussian random matrix. Therefore, the BRPS contributes to the implementation of compressive sensing with low cost, low power consumption, less memory requirement, and better reconstruction.