Imaging Technology Based On Compressive Sensing

Compressive sensing is an emerging sampling theory.It can break through the limitation of the Nyquist sampling theorem,and accurately reconstruct the original signal with minimal sampling data.The application of compressive sensing theory to imaging technology can effectively reduce the imaging time and improve the imaging quality.In this paper,we focus on the research of compressive sensing imaging technology with atomic force microscope(AFM)and magnetic resonance imaging ceremony(MRI).AFM is a high-precision test instrument on the nanometer scale.It can perform three-dimensional surface topography imaging for a variety of materials.However,limited by the mechanical structure and measurement principle of the AFM,the imaging range is small and the imaging speed is slow.High speed AFM is the inevitable trend of its development.Compressive sensing technology can effectively reduce the number of AFM measurement points,significantly reduce the AFM imaging time,reduce the interaction between the probe tip and the sample,and avoid sample damage and probe wear.In this paper,we focus on the study of AFM imaging technology based on compressive sensing,and analyze the effects of different sample rates and sample morphologies on the quality of the AFM reconstructed image.On this basis,we analyze the effects of different scan patterns(random scan pattern,SRM scan pattern,spiral scan pattern,raster scan pattern and square-shape scan pattern)on the measurement results,and analyze the effects of different reconstruction algorithms(11-1s algorithm,GPSR algorithm,TVAL3 algorithm and IHT algorithm)on the AFM image reconstruction.In order to achieve ultra-high resolution compressive sensing AFM imaging,we propose AFM imaging technology based on block compressive sensing in this paper.By introducing the idea of overlapping blocks,the block effect caused by block processing is reduced or even eliminated.We analyze the effect of block size and overlap rate on the reconstruction of AFM images and compare this method with the traditional compressive sensing imaging technology.AFM imaging technology based on block compressive sensing can effectively increase the AFM imaging range.MRI is an important medical imaging device in clinical medicine.Because of the imaging characteristics of MRI,its imaging time is too long,which will cause some inconvenience and harmful to the patient.Using compressive sensing technology to downsample K-space data of magnetic resonance can effectively shorten the imaging time without degrading the imaging quality.In this paper,three undersampling patterns(cartesian sampling pattern,pseudo radial sampling pattern and 2D sampling pattern)were used to perform downsampling simulation experiments,and three kinds of reconstruction algorithms(TVAL3 algorithm,Spa rse-MRI algorithm,and GPSR algorithm)were used to reconstruct the downsampling data.Compressive sensing achieves fast MRI.