Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province

Hefei, China

Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province

Hefei, China
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Zhang C.,Anhui University | Zhang C.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Ou S.,Anhui Light Industry Polytechnic | Shen C.,Anhui University | And 3 more authors.
Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) | Year: 2016

In order to solve the problem raised in compressive sensing theory that the classical measurement matrices (random Gaussian, random Bernoulli, et al.) does not achieve the optimal performance, a novel method was proposed for the measurement matrix optimization based on singular value decomposition. In this method, the singular value decomposition was introduced to optimize the general linear measurement model in compressive sensing, i.e.measurement matrix and corresponded measurement vector, and then the original signal sparse signal was reconstructed by the optimized linear measurement model. Numerical results for the classical random Gaussian measurement matrix and random Bernoulli measurement matrix demonstrated that the proposed method can significantly increase the reconstruction probability of successful recovery and is more robust to Gaussian noise and applicable to the general linear measurement system, which can successfully achieve the separation of the measurement matrix and the reconstruction matrix, and make the reconstruction matrix close to the most excellent configuration without the any model change at the front end of the measurement system. © 2016, Editorial Department of Journal of Sichuan University (Engineering Science Edition). All right reserved.


Wang Y.,Anhui University | Shen C.,Anhui University | Zhang C.,Anhui University | Zhang C.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | And 2 more authors.
Zhongguo Jiguang/Chinese Journal of Lasers | Year: 2012

Color holographic display is an important goal of holographic display research. Color holographic display technology using RGB lasers is studied, and color holographic display method based on space division multiplexing is proposed. Both the size and center of holographic optoelectronic reconstruction image depend on the wavelength of RGB lasers. The method by adjusting the original sizes of the RGB components of color images and adding digital blazed grating to achieve the coincidences of the sizes and centers of RGB reconstructed images is proposed. The color holographic display system with space division multiplexing method is developed, and hologram generated by 24-bit computer is added to spatial light modulator to reconstruct the color images by the advanced physics setup. Experimental results demonstrate the feasibility of the method proposed.


Zhang C.,Anhui University | Zhang C.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Shen C.,Anhui University | Cheng H.,Anhui University | And 3 more authors.
Zidonghua Xuebao/Acta Automatica Sinica | Year: 2015

Compressed holography is an emerging 3D reconstruction technique, which bridges the gap between compressed sensing (CS) theory and Gabor's holography, especially for rebuilding 3D objects from a single-frame 2D holography measurement data. In this paper, the single-wavelength settings in compressed holography are extended to the multi-wavelength, and an improved compressed color holography imaging method is proposed, and a compressed measurement model in multi-wavelength case is established. Utilizing sparse prior knowledge of an object, a multi-wavelength 3D object can be reconstructed effectively from single-frame 2D color holography data of the object, so as to suppress the twin image and the defocus image due to multilayer slices and thus improve high quality reconstruction. Numerical results have demonstrated the effectiveness of our method. Copyright © 2015 Acta Automatica Sinica. All rights reserved.


Zhang C.,Anhui University | Zhang C.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Cheng H.,Anhui University | Zhang F.,Anhui University | And 2 more authors.
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2014

Super resolution (SR) is being considered as one of the “holy grails” of optical imaging and image processing. Different from the registration error and costly problem faced in multiple subpixel image registration fusion method to achieve super-resolution, this paper introduces the compressive sensing theory into super-resolution imaging, which benefit from the general sparse representation of most nature images, and proposes a novel single-exposure frequency-domain amplitude encoding compressive imaging method. Exploiting the 4-f Fourier optics architecture for modulating the image information by the 0/1 amplitude randomly in the frequency domain, low-resolution CCD device can then be used to records the corresponding measured values by integral downsampling and finally apply optimization methods to reconstruct the original high-resolution images from small number of measured values. Simulation experiments demonstrate that the 2D image information can be effectively acquired and reconstruction from the measured data by our proposed method. In addition, our method can effectively deal with large-scale image compressive imaging problem and thus has an important application prospects.


Zhang C.,Anhui University | Cheng H.,Anhui University | Cheng H.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Shen C.,Anhui University | And 2 more authors.
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | Year: 2012

Compressive imaging is a novel imaging method based on compressive sensing theory, the key idea is that it can reconstruct original scene precisely with far fewer measurements than Nyquist samples if the scene is sparse/compressible; Constructing an appropriate measurement matrix easy to realize random linear measurement of an image is one of the key points of practical compressive sensing. In this paper, analyzing the existing Bernoulli and Circulant matrices, a novel sparse trinary circulant measurement matrix with random spacing for phase mask is proposed. Simulation results show that novel phase mask matrices, compared to Bernoulli and Bernoulli-Circulant (BC) phase mask matrices, have the same signal-to-noise ratio; But with the number of independent random variables and the number of non-zeros entries a dramatically reduction, which is more conducive to data transmission and storage; more importantly that is easy to hardware implementation and the reconstructed time is only about 20%~50% of that of original matrices, which has a significance effects on practical compressive sensing.


Zhang C.,Anhui University | Shen C.,Anhui University | Cheng H.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Zhang F.,Anhui University | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2015

In classical compressive holography (CH), which based on the Gabor holography setup, two nonlinear terms are inherent in the intensity recorded by a 2D detector arrays, the DC term and the squared field term. The DC term (the term at the origin) can be eliminated by filtering the Fourier transform of the interference irradiance measurements using appropriate high-pass filter near the zero frequency. The nonlinearity caused by the squared field term can be neglected and modeled as a error term in the measurement. However, the above assumptions are significantly limited, which yields the degradation of reconstruction quality. In this paper, an novel scheme using phase-shifting method is presented. To accurately recover the complex optical field caused by the propagation of the object, without the influence of the DC term and the squared field term, a very effective method for removing these two terms is introduced. The complex optical field of the 3D object and the complex optical field at the detector plane can be precisely represented by a linear mapping model. The complex optical field at the recorder plane is obtained by phase-shifting interferometry with multiple shots. Then, the corresponded complex optical field at the detector plane can be successfully extracted from multiple captured holograms using conventional four phase-shifting interferometry. From such complex optical field at the record plane, including the amplitude and phase information, the complex optical field of the 3D object can be reconstructed via an optimization procedure. Numerical results demonstrate the effectiveness of our proposed method. © 2015 SPIE.


Cheng H.,Anhui University | Zhang C.,Anhui University | Wei S.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Wang W.,Anhui University
Guangdianzi Jiguang/Journal of Optoelectronics Laser | Year: 2012

Phase retrieval technique using the directly measured intensity distribution to recover phase information and reconstruct the wave function is an important area of optics and image processing. Taking advantage of the existing phase retrieval based on transport equation of intensity, the light propagation model consistent with the principle of general camera images in natural light conditions is established, the corresponding optical data collection platform is designed and a phase retrieval method in this new model is derived. Real experimental results verify that this new phase retrieval method is reasonable and correct. The application of traditional phase retrieval algorithm on transport equation of intensity is extended to the holographic display and other macro-areas.


Zhang C.,Anhui University | Cheng H.,Anhui University | Cheng H.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Zhang F.,Anhui University | And 2 more authors.
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2013

Compressed Imaging (CI) is one of the most important research area of compressed sensing. Analyzing the constraints on actual measurement matrix and measurement values in CI, a frequency domain phase encoding CI method is proposed, which can b e physically realized based on 4-f optical architecture. This method exploits tw o-way optical architecture compensated for the phase-encoding CI to implement the value non-negative for recording, and then accurately recover the original i mage from the measured values, to resolve inconsistencies between the theoretical requirements and physical constraints in CI. With measured values can be obtaine d in a single exposure, such method can reconstruct the original image precisely without additional information, and is a very practical scheme for physical reali zation of CI. Simulation experiments demonstrate that our proposed method can eff ectively capture compressed measurements of image and achieve super-resolution reconstruction.


Zhang C.,Anhui University | Cheng H.,Anhui University | Cheng H.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | Zhang F.,Anhui University | Wei S.,Anhui University
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | Year: 2014

One of the goals of optical imaging and image processing is super-resolution imaging. In order to reduce the registration error and costly problem facing in multiple sub-pixel image registration fusion method to achieve super-resolution, a compressive sensing method is introduced for super-resolution imaging, it benefits from the general sparse representation feature of most nature images. Based on the classical 4-f optical architecture, the phase will contain more information than the amplitude in frequency domain, a compressed imaging method with pure phase modulation in the frequency domain is proposed. The original high-resolution image information can be recovered from the low-dimensional measurements recorded with a single exposure by various algorithms. Numerical results demonstrate that the proposed can effectively achieve random modulation of image information and high-quality reconstruction, which can be considered as a promising scheme for physics implementation of compressed imaging with high reconstruction signal to noise ratio and less reconstruction time, especially for large-scale image.


Guangdong D.,Anhui University | Cheng Z.,Anhui University | Hong C.,Anhui University | Hong C.,Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

Depth information of the image is really necessary information to reconstruct a 3-dimensional object. The classical methods of depth estimation are generally divided into two categories: active and passive methods. The active methods requires the additional lighting equipment, passive methods also have a series of problems. They require a plurality of images obtained by capturing a plurality of viewpoints, and determine the locating occlusion boundary, etc., and hence the depth estimation has been a challenging problem in the research field of computer vision.1 Because of the depth information of the image has a natural sparse features, this paper uses a passive approach, the signal of sparse priori based on compressed sensing theory is used to estimate the depth of the image, without capturing multiple images, using a single input image can obtain a high quality depth map. Experimental results show that the depth map obtaining by our method, compared to the classical passive method, the contour sharpness, the depth of detail information and the robustness of noise are more advantages. The method also can be applied to re-focus the defocused images, and automatic scene segmentation and other issues, ultimately may have broad application prospects in the reconstruction of true 3-dimensional objects. © 2014 SPIE.

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