Yutong Jiang

Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method

To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constraint. Secondly, the EM algorithm is improved by combining the AO imaging system parameters and regularization technique. A cost function for the joint-deconvolution multiframe AO images is given, and the optimization model for their parameter estimations is built. Lastly, the image-restoration experiments on both analog images and the real AO are performed to verify the recovery effect of our algorithm. The experimental results show that comparing with the Wiener-IBD or RL-IBD algorithm, our iterations decrease 14.3% and well improve the estimation accuracy. The model distinguishes the PSF of the AO images and recovers the observed target images clearly.

Image Dehazing Using Adaptive Bi-Channel Priors on Superpixels

Abstract Recently, a number of image dehazing methods are developed based on dark channel prior which is simple yet effective. In order to compensate for any failure on the use of dark channel prior in white regions and bright channel prior in black regions, an image dehazing method using a novel adaptive bi-channel priors on superpixels is presented in this paper. In the proposed method, a haze image is converted to the hue, saturation, and value space, and the linearly transformed thresholds on saturation and value are used to detect any white and black pixels. Using superpixels as local regions, the local transmission and atmospheric light values are estimated more reliably and efficiently by combining the dark and bright channel priors (bi-channel priors). Furthermore, adaptive bi-channel priors are developed to rectify any incorrect estimations on transmission and atmospheric light values for white and black pixels that fail to satisfy the assumptions of the bi-channel priors. After applying our dehazing method, the white and black pixels on the restored image are with excellent fidelity. Experimental results demonstrate that our proposed method performs better for restoring images in terms of both quality and execution speed than the current state-of-the-art dehazing methods.

Orientation-guided geodesic weighting for PatchMatch-based stereo matching

We propose an orientation-guided geodesic weighting (OGGW) strategy for local stereo matching.We propose a method of cost volume filtering combining a multipoint LPA method with our OGGW strategy.We propose a PatchMatch filter with curved surface fitting (PMF-CS) to obtain a disparity map with sub-pixel accuracy. Recently, PatchMatch-based methods for local stereo matching are experiencing great progress with the use of compact and over-segmented regions that have similar intensities or colors. Using patches as support regions, this paper proposes an orientation-guided geodesic weighting (OGGW) strategy to search for an approximate shortest path from a support pixel in the patch to a pixel of interest along a guided orientation. The OGGW is computed by accumulating intensity differences or color dissimilarities between connected pixels along the path. After obtaining matching cost updates by model fitting, the OGGW is used for weighted averaging on the updated costs to obtain a filtered cost volume. In addition, a new filtering method that combines the PatchMatch filter with curved surface fitting (PMF-CS) is presented in this paper. Curved surface fitting along with outliers removal is carried out to seek for a reliable regression model for estimating the disparities on a patch and to achieve a disparity map with sub-pixel accuracy. We conduct a number of experiments to evaluate the performances of OGGW and PMF-CS on cost volume filtering and disparity estimation. Experimental results show that our algorithm produces accurate stereo matching results and outperforms the current state-of-the-art PatchMatch-based methods.

Fog Density Estimation and Image Defogging Based on Surrogate Modeling for Optical Depth

In order to estimate fog density correctly and to remove fog from foggy images appropriately, a surrogate model for optical depth is presented in this paper. We comprehensively investigate various fog-relevant features and propose a novel feature based on the hue, saturation, and value color space, which correlate well with the perception of fog density. We use a surrogate-based method to learn a refined polynomial regression model for optical depth with informative fog-relevant features, such as dark-channel, saturation-value, and chroma, which are selected on the basis of sensitivity analysis. Based on the obtained accurate surrogate model for optical depth, an effective method for fog density estimation and image defogging is proposed. The effectiveness of our proposed method is verified quantitatively and qualitatively by the experimental results on both synthetic and real-world foggy images.In order to estimate fog density correctly and to remove fog from foggy images appropriately, a surrogate model for optical depth is presented in this paper. We comprehensively investigate various fog-relevant features and propose a novel feature based on the hue, saturation, and value color space, which correlate well with the perception of fog density. We use a surrogate-based method to learn a refined polynomial regression model for optical depth with informative fog-relevant features, such as dark-channel, saturation-value, and chroma, which are selected on the basis of sensitivity analysis. Based on the obtained accurate surrogate model for optical depth, an effective method for fog density estimation and image defogging is proposed. The effectiveness of our proposed method is verified quantitatively and qualitatively by the experimental results on both synthetic and real-world foggy images.

Study on tip leakage vortex cavitating flows using a visualization method

Experimental investigations of unsteady cavitating flows in a hydrofoil tip leakage region with different gap sizes are conducted to highlight the development of gap cavitation. The experiments were taken in a closed cavitation tunnel, during which high-speed camera had been used to capture the cavitation patterns. A new visualization method based on image processing was developed to capture time-dependent cavitation patterns. The results show that the visualization method can effectively capture the cavitation patterns in the tip region, including both the attached cavity in the gap and the tip leakage vortex (TLV) cavity near the trailing edge. Moreover, with the decrease of cavitation number, the TLV cavity develops from a rapid onset-growth-collapse process to a continuous process, and extends both upstream and downstream. The attached cavity in the gap develops gradually stretching beyond the gap and combines with the vortex cavity to form the triangle cavitating region. Furthermore, the influences o...

Complex Segregation Analysis Provides Evidence for Autosomal Dominant Transmission in the Chinese Han Families with Ankylosing Spondylitis

Introduction Familial aggregation of ankylosing spondylitis (AS) has been frequently noticed. However, the mode of inheritance in AS remains poorly understood. Our aim was to determine the mode of inheritance best fitting the observed transmission pattern of AS families. Methods Families with 5 or more AS patients diagnosed with 1984 modified New York criteria were recruited. We performed complex segregation analysis for a binary trait in regressive multivariate logistic models. The inheritance models, including sporadic, major gene, environmental, general, and other 9 models, were compared by likelihood ratio tests and Akaikes Information Criterion. Results This research included 9 Chinese Han AS families with a total number of 315 persons, including 74 patients. First, familial association was determined. Sporadic with familial association model was rejected when compared with either the general model or the homogeneous general model (p < 0.001). The environmental model was also rejected when compared with general models (p < 0.02). Mendelian dominate mode fitted best in 5 AS families, while Tau AB free model best explained the mode of inheritance in these AS families. Conclusion This study provided evidence in support of Mendelian dominant mode and firstly discovered a non-Mendelian mode called tau AB free inheritance mode in AS.