Hongqing Zhu
Southeast University
Imaging phantomOrthogonal polynomialsAlgorithmCombinatoricsRandom variableMathematical optimizationInverse problemOrthogonal functionsIterative reconstructionVelocity MomentsArtificial intelligenceCoordinate descentIterative methodPixelNumerical stabilityExpectation–maximization algorithmProjection (set theory)Anisotropic diffusionOpen problemReconstruction algorithmApplied mathematicsMinimum cross entropyComputer visionMathematicsSequenceFuzzy setDiscrete orthogonal polynomialsImage qualityRate of convergenceOrthonormal basisFuzzy logicNorm (mathematics)Method of moments (statistics)Hahn polynomialsMathematical problemRegularization (mathematics)Noise (video)
19Publications
10H-index
524Citations
Publications 19
Newest
#1Yi Liu (North University of China)H-Index: 7
#2Hong Shangguan (North University of China)H-Index: 5
Last. Zhiguo Gui (North University of China)H-Index: 10
view all 6 authors...
It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current,...
20 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Jean-Louis Coatrieux (University of Rennes)H-Index: 25
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In this paper, we introduce a set of discrete orthogonal functions known as dual Hahn polynomials. The Tchebichef and Krawtchouk polynomials are special cases of dual Hahn polynomials. The dual Hahn polynomials are scaled to ensure the numerical stability, thus creating a set of weighted orthonormal dual Hahn polynomials. They are allowed to define a new type of discrete orthogonal moments. The discrete orthogonality of the proposed dual Hahn moments not only ensures the minimal information redu...
136 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Jean Louis Coatrieux (University of Rennes)H-Index: 10
view all 5 authors...
Discrete orthogonal moments such as Tchebichef moments have been successfully used in the field of image analysis. However, the invariance property of these moments has not been studied mainly due to the complexity of the problem. Conventionally, the translation and scale invariant functions of Tchebichef moments can be obtained either by normalizing the image or by expressing them as a linear combination of the corresponding invariants of geometric moments. In this paper, we present a new appro...
84 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Limin Luo (SEU: Southeast University)H-Index: 29
view all 5 authors...
The basic mathematical problem behind PET is an inverse problem. Due to the inherent ill-posedness of this inverse problem, the reconstructed images will have noise and edge artifacts. A roughness penalty is often imposed on the solution to control noise and stabilize the solution, but the difficulty is to avoid the smoothing of edges. In this paper, we propose two new types of Bayesian one-step-late reconstruction approaches which utilize two different prior regularizations: the mean curvature ...
16 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Jean-Louis Coatrieux (University of Rennes)H-Index: 25
view all 5 authors...
Discrete orthogonal moments are powerful tools for characterizing image shape features for applications in pattern recognition and image analysis. In this paper, a new set of discrete orthogonal moments is proposed, based on the discrete Racah polynomials. In order to ensure numerical stability, the Racah polynomials are normalized, thus creating a set of weighted orthonormal Racah polynomials, to define the so-called Racah moments. This new type of discrete orthogonal moments eliminates the nee...
147 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Limin Luo (SEU: Southeast University)H-Index: 29
view all 5 authors...
Iterative image reconstruction algorithms have been widely used in the field of positron emission tomography (PET). However, such algorithms are sensitive to noise artifacts so that the reconstruction begins to degrade when the number of iterations is high. In this paper, we propose a new algorithm to reconstruct an image from the PET emission projection data by using the conditional entropy maximization and the adaptive mesh model. In a traditional tomography reconstruction method, the reconstr...
9 CitationsSource
#1Ting Xia (SEU: Southeast University)H-Index: 6
#2Hongqing Zhu (SEU: Southeast University)H-Index: 10
Last. Limin LuoH-Index: 29
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A new set, to our knowledge, of orthogonal moment functions for describing images is proposed. It is based on the generalized pseudo-Zernike polynomials that are orthogonal on the unit circle. The generalized pseudo-Zernike polynomials are scaled to ensure numerical stability, and some properties are discussed. The performance of the proposed moments is analyzed in terms of image reconstruction capability and invariant character recognition accuracy. Experimental results demonstrate the superior...
51 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Limin Luo (SEU: Southeast University)H-Index: 29
view all 5 authors...
Iterative algorithms such as maximum likelihood-expectation maximization (ML-EM) become the standard for the reconstruction in emission computed tomography. However, such algorithms are sensitive to noise artifacts so that the reconstruction begins to degrade when the number of iterations reaches a certain value. In this paper, we have investigated a new iterative algorithm for penalized-likelihood image reconstruction that uses the fuzzy nonlinear anisotropic diffusion (AD) as a penalty functio...
8 CitationsSource
#1Hongqing Zhu (SEU: Southeast University)H-Index: 10
#2Jian Zhou (SEU: Southeast University)H-Index: 12
Last. Limin Luo (SEU: Southeast University)H-Index: 29
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In this paper, we present a novel image reconstruction method based on weighted least squares (WLS) objective function for positron emission tomography (PET). Unlike a usual WLS algorithm, the proposed method, which we call it SA-WLS, combines the SAGE algorithm with WLS algorithm. It minimized the WLS objective function using single coordinate descent (SCD) method in a sequence of small ''hidden'' data spaces (HDS). Although SA-WLS used a strategy to update parameter sequentially just like comm...
8 CitationsSource
#1Jian Zhou (SEU: Southeast University)H-Index: 12
#2Huazhong Shu (SEU: Southeast University)H-Index: 34
Last. Limin Luo (SEU: Southeast University)H-Index: 29
view all 5 authors...
Orthogonal moments are recognized as useful tools for object representation and image analysis. It has been shown that the recently developed discrete orthogonal moments have better performance than the conventional continuous orthogonal moments. In this paper, a new set of discrete orthogonal polynomials, namely Hahn polynomials, are introduced. The related Hahn moment functions defined on this orthogonal basis set are investigated and applied to image reconstruction. In experiments, the Hahn m...
57 CitationsSource