Zhang Leihong

Study of Spectral Reflectance Reconstruction Based on an Algorithm for Improved Orthogonal Matching Pursuit

Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.

Spectral reflectance recovery from a white-balanced RGB image based on the algorithm of compressive sensing

In this work we study the methods for reconstructing spectral reflectances of images. To reproduce the spectral reflectance more accurately and the colours more realistically, we obtain a so-called average transformation matrix, using! a series of different modulated light sources to illuminate a standard whiteboard. For eliminating the influence of those light sources on RGB images, we first use, a white-balance algorithm to standardize the scene information, thus obtaining a uniform RGB image with different sources. Then we map the RGB image onto the spectral reflectance basing on a compressive, sensing algorithm and the principal component analysis and, finally, reconstruct the spectral reflectance of the testing sample. We compare the reconstruction accuracies of our compressive sensing algorithm based on white-balance calibration with the results derived using a pseudo-inverse method and a traditional compressive sensing algorithm. Our simulation results show that, under the same conditions of reconstruction, the residual errors and the colour difference resulting from our improved algorithm are less than those produced by the other two algorithms. In other words, the reconstruction algorithm suggested by us outperforms the other methods and can provide better performance of image colour reproduction.

Study on the key technology of spectral reflectance reconstruction based on the weighted measurement matrix

In order to reconstruct the spectral reflectance accurately, a new method of spectral reflectance reconstruction based on the weighted measurement matrix is proposed in this paper. By optimizing the measurement matrix between spectral reflectance and the response of a camera, the method can improve the reconstruction accuracy. The new method is a combination of three kinds of common reflectance reconstruction methods, which are the pseudo inverse method, the Wiener estimation method and the principal component analysis method. The new measurement matrix can be achieved after weighting the measurement matrices of these three methods to reconstruct the spectral reflectance. What is more, the weights of the three methods can be obtained by minimizing the color difference. Results show that the CIE1976 color difference and RMSE value of the weighted reconstructed spectra are less than that of three common reconstruction methods. The spectral matching accuracy GFC of the method is higher than 0.99 and its reconstruction accuracy is high.

The study of key technology on spectral reflectance reconstruction based on the algorithm of adaptive compressive sensing

In order to improve the reconstruction accuracy and reduce the workload, the algorithm of compressive sensing based on the iterative threshold is combined with the method of adaptive selection of the training sample, and a new algorithm of adaptive compressive sensing is put forward. The three kinds of training sample are used to reconstruct the spectral reflectance of the testing sample based on the compressive sensing algorithm and adaptive compressive sensing algorithm, and the color difference and error are compared. The experiment results show that spectral reconstruction precision based on the adaptive compressive sensing algorithm is better than that based on the algorithm of compressive sensing.

Study of key technology of ghost imaging via compressive sensing for a phase object based on phase-shifting digital holography

In this article, the algorithm of compressing sensing is used to improve the imaging resolution and realize ghost imaging via compressive sensing for a phase object based on the theoretical analysis of the lensless Fourier imaging of the algorithm of ghost imaging based on phase-shifting digital holography. The algorithm of ghost imaging via compressive sensing based on phase-shifting digital holography uses the bucket detector to measure the total light intensity of the interference and the four-step phase-shifting method is used to obtain the total light intensity of differential interference light. The experimental platform is built based on the software simulation, and the experimental results show that the algorithm of ghost imaging via compressive sensing based on phase-shifting digital holography can obtain the high-resolution phase distribution figure of the phase object. With the same sampling times, the phase clarity of the phase distribution figure obtained by the algorithm of ghost imaging via compressive sensing based on phase-shifting digital holography is higher than that obtained by the algorithm of ghost imaging based on phase-shift digital holography. In this article, this study further extends the application range of ghost imaging and obtains the phase distribution of the phase object.

Research on the deformation characteristic of the sheet by oblique angle laser shock

Normally, the deformation of laser shock forming on metal sheet requires the laser shock wave to be vertical to the surface of the sheet. But the condition is hard to meet when processing curved surfaces. Therefore it is necessary to clarify the principle of oblique angle laser shock. In this paper, a deformation formula is deduced based on the theoretical analysis of oblique angle laser shock. Through simulation, it turned out that with increasing incidence angle, the vertical component of the shock wave decreased, while the deformation in the depth of the sheet decreased, meanwhile, with increasing incidence angle, the horizontal component of the shock wave increased, while the eccentricity in the transverse direction of the sheet decreased. A high-power Nd-glass laser and the material LD31(6063) was used in the experiment. The deformation of the sheet was measured and the experimental result accorded with the simulation result. The research of this paper could provide a reference for laser processing when the surface cannot be shocked in the vertical direction.