Investigations and implementation of reconstruction algorithms for video surveillance in wireless sensor networks

Abstract

The increase in voluminous data transmission has provoked the need for compressing multimedia data to be transmitted efficiently over wireless newlinesensor networks with ease Compression of data reduces storage space newlinebandwidth time complexity etc lead to improvement in the lifetime of nodes newlinein the network Generally traditional compression procedures are based on the newlineNyquist criterion which implies perfect recovery at the receiver is possible only newlineif the number of samples considered for compression is equal to at least twice the highest frequency available in the data When the data increases in volume then the traditional methods are disadvantageous since the compressed samples will also be voluminous. In order to overcome this backslide compressed sensing has been proposed The last decade has seen immense development in the field of compressed sensing which projects the captured data to a lower dimensional space, which subdues the necessity of Nyquist criteria These diminished values are sent to the receiver where special reconstruction procedures recover the original signal newline newline