The algorithm of image representation and reconstruction based on compressed sensing with composite measurement

Compressed sensing (CS) technology has been shown to be able to reduce the amount of sampled data effectively. In this paper, an algorithm of image representation and reconstruction is proposed based on compressed sensing with composite measurement. Being transformed into the wavelet domain, composite observations could be handled according to the distribution properties of the image wavelet domain representation, which means the wavelet coefficients components could be divided into one dense component and a number of sparse components, and different component can be measured with different noiselet observations. In the image reconstruction process, due to the measurement relation between the original image and the observations is established, we can use the total variation minimization method to reconstruct the original image. Experimental results demonstrate that the proposed algorithm is competitive to the existed similar algorithms with higher quality of image reconstruction.