Abstract: The construction of measurement matrixes is one of the most significant issues in the compressed image/ video sensing (CIS/CVS).In order to overcome the uncertainty of random measurement matrixes and the heavy pressure in transmission and to improve the reconstruction quality in encoder ends,a novel deterministic sparse measurement matrix named adjacent-pixel-based matrix (APM) is constructed for the CIS/CVS，based on the cor- relation of adjacent pixels.During the APM construction,first,an annulus choosing method is proposed to uni- formly select the target points in the measured image block.Then,the Gaussian probability density function is adopted to distribute weights to the elements of the measurement matrix corresponding to the adjacent pixels of the target points,so as to ensure that each measurement only contains the information of one target point and its adja- cent pixels.Applying the measurement from the proposed APM in the image or video reconstruction helps take ad- vantage of the correlation between adjacent pixels and avoid the interference from the other further pixels,and thus a higher reconstruction quality can be achieved.Simulation results show that，in comparison with other classical and novel measurement matrixes in the literature,the proposed APM achieves higher image/video reconstruction quality with lower reconstruction complexity,and that it is of a wider range of application.

Key words: compressed sensing, measurement matrix, spatial correlation, image/video compression