Dobrucalı, OğuzcanBarshan, Biilur2016-02-082016-02-082011-08-092219-5491http://hdl.handle.net/11693/28312Date of Conference: 29 Aug.-2 Sept. 2011Conference name: 19th European Signal Processing Conference, 2011Modeling and representing 3-D environments require the transmission and storage of vast amount of measurements that need to be compressed efficiently. We propose a novel compression technique based on compressive sensing for 3-D range measurements that are found to be correlated with each other. The main issue here is finding a highly sparse representation of the range measurements, since they do not have highly sparse representations in common domains, such as the frequency domain. To solve this problem, we generate sparse innovations between consecutive range measurements along the axis of the sensor's motion. We obtain highly sparse innovations compared with other possible ones generated by estimation and filtering. Being a lossy technique, the proposed method performs reasonably well compared with widely used compression techniques. © 2011 EURASIP.English3-D environmentsCompression methodsCompression techniquesCompressive sensingEstimation and filteringFrequency domainsIndoor environmentLaser range scanLossy techniquesRange measurementsSparse representationSignal reconstructionThree dimensionalConference Paper