Title :
Compressive measurements with integrated sensing, compression and data processing — Initial study
Author :
Przelaskowski, Artur ; Jozwiak, Rafal
Author_Institution :
Inst. of Radioelectron., Warsaw Univ. of Technol., Warsaw, Poland
Abstract :
In this work, modifications to the paradigm of compression using the concept of compressive sensing was proposed. Procedure of detail estimation based on image coarse approximation from linear cosine measurements was optimized. These details were used to determine the most advantageous locations of fixed noise let measurements. Adaptively optimized calculation of sparsity pattern over significant singularities enhanced noise let measurement efficiency. Experimentally verified effectiveness of the proposed sensed compression method has shown significant improvement in compression efficiency compared to reference methods.
Keywords :
compressed sensing; data compression; function approximation; image coding; compressive measurement; compressive sensing; data compression; enhanced noiselet measurement; image coarse approximation; integrated sensing; linear cosine measurement; sparsity pattern; Approximation methods; Image coding; Image reconstruction; Noise measurement; Sensors; Transforms; Vectors;
Conference_Titel :
Picture Coding Symposium (PCS), 2012
Conference_Location :
Krakow
Print_ISBN :
978-1-4577-2047-5
Electronic_ISBN :
978-1-4577-2048-2
DOI :
10.1109/PCS.2012.6213325
