ABSTRACT
Tremendous growth in microelectronics has led to the development of low-cost and miniaturized cameras which paved way for the evolution of wireless multimedia sensor networks. This chapter focuses on efficient strategies to improve the sampling and reconstruction process in compressed sensing. Performance analysis for the proposed content-based model is evaluated based on the reduction in the number of measurements, image quality, and bit rate. The greedy algorithms use this correlation between the signal and the columns of the measurement matrix as a measure to find the elements with nonzero coefficients. The chapter introduces the two-measurement matrix algorithm and an enhanced orthogonal matching pursuit algorithm. The acceptance range is used to find the wrongly detected columns, as their entry reduces the projection coefficient values. Suppression factor is used to suppress the wrongly detected columns from entering into the support set again. It enables easy convergence toward the correct support set.
