DPCM Block-based Compressed sensing with frequency domain filtering and Lempel-Ziv-Welch compression

Block Compressed Sensed (BCS) images reconstructed by the Smoothed Projected Landweber (SPL) equations are severely degraded in visual quality. This work focuses on removal of the noise present in the BCS - SPL reconstructed image. For noise removal the nature of the noise is studied first. A suitable frequency domain filter to mitigate this noise is proposed in this work. Differential Pulse Coded Modulation after coupling with Blocked Compress Sensing and the proposed filtering shows significant improvement in the result compared to many other similar techniques where generally smoothing filters or no filters are used. Along with Differential Pulse Coded Modulation, this work proposes the use of Lempel-Ziv-Welch channel coding technique for further compression of data. Significant compression is achieved for medical images compared to other channel coding techniques by the incorporation of LZW.