This paper proposes efficient algorithms to enhance the nearfield electromagnetic imaging of human head. Forward problem is modeled using SAM head phantom with brain tumor anomalies, surrounded by a circular applicator antenna array. Scattered signals are compressively sensed (CS) at a limited number of sensing positions, and the sensed signals are preprocessed efficiently using a proposed novel technique to maximize information extraction. A dictionary is formed and then implemented in CS based inverse problem analysis. Reconstructed images are enhanced using new post-processing techniques to improve the spatial resolution. Image quality is analyzed using the quality metric in terms of peak signal-to-noise ratio (PSNR). The quality of the reconstructed images and the corresponding PSNR values reveals the validity of the imaging techniques.Index Terms-Nearfield imaging, electromagnetic imaging, head imaging, compressed sensing, SAM phantom.This full text paper was peer-reviewed at the direction of IEEE Instrumentation and Measurement Society prior to the acceptance and publication.978-1-4799-6477-2/15/$31.00 ©2015 IEEE