scholarly journals A New Error Concealment Algorithm Based on Directional Texture Synthesis

2012 ◽  
Vol 6-7 ◽  
pp. 309-314
Author(s):  
Jiang Xin Zhang ◽  
Jin Xie
Keyword(s):  
Image Reconstruction ◽  
Confidence Level ◽  
Error Concealment ◽  
Texture Synthesis ◽  
Experimental Results ◽  
Interpolation Algorithm ◽  
Structure Information ◽  
Video Images ◽  
Directional Texture

In this paper, we propose a novel directional texture synthesis based error concealment algorithm to recover damaged video images. It uses the confidence level and structure information to calculate the priority of patch, which contributes to improve the ability to select the best matching block when the damaged area is very large. The JM86 model of H.264 standard is used to evaluate the algorithm. And experimental results show that our algorithm achieved a better image reconstruction results than the improved Multi-directional texture interpolation algorithm, with 1.2 to 1.4dB gain in PSNR and 0.5 percent to 1 percent gain in SSIM.

An Improved Error Concealment Technique Based on Multi-View Video Coding

2014 ◽  
Vol 599-601 ◽  
pp. 1383-1386
Author(s):  
Hai Bo Liu ◽  
Xiao Sheng Huang
Keyword(s):  
Image Reconstruction ◽  
Video Coding ◽  
Spatial Correlation ◽  
Error Concealment ◽  
Motion Vector ◽  
Temporal Correlation ◽  
Experimental Results ◽  
Matching Algorithm ◽  
Video Images ◽  
Disparity Vector

In this paper, we propose a improved error concealment technique based on multi-view video coding to recover damaged video images. At first,It uses BMA(Boundary Matching Algorithm) method to recover the lost or erroneously received motion vector or disparity vector,then combining inter-view correlation, temporal correlation and spatial correlation to recover the lost blocks. The JM12.0 model of H.264 standard is used to evaluate the algorithm. And the experimental results show that our algorithm achieved a better image reconstruction.

Research on Improved Spline Interpolation Algorithm in Super-Resolution Reconstruction of Video Image

2013 ◽  
Vol 380-384 ◽  
pp. 3722-3725
Author(s):  
Xiang Hua Hou ◽  
Hong Hai Liu
Keyword(s):  
Spline Interpolation ◽  
Super Resolution ◽  
Cubic Spline ◽  
High Order ◽  
Experimental Results ◽  
Interpolation Algorithm ◽  
Cubic Spline Interpolation ◽  
Video Images ◽  
The Common ◽  
Order Spline

When low-spline interpolation algorithm is adopted by super-resolution reconstruction for video images, there are some defects, such as saw tooth and blur edge, if the result image is magnified. In this paper, high-order spline interpolation algorithm is introduced and it is optimized. Firstly, the common low-spline interpolation algorithms are analyzed and their shortcomings are pointed out. Then cubic spline interpolation algorithm is discussed. If the image is rotated by cubic spline interpolation algorithm, the magnified image may be not correctly displayed and the image can not be registered in super-resolution reconstruction. Finally, the cubic spline algorithm has been improved. Experimental results show that the improved cubic spline interpolation algorithm can not only eliminate the edge blur and saw tooth, but also do registration in reconstruction when image is rotating.

Adaptive Error Concealment Technology Based on H.264 for Digital Satellite Set-Top Boxes

2013 ◽  
Vol 273 ◽  
pp. 784-789
Author(s):  
Xiao Juan Tao ◽  
Ling Wang
Keyword(s):  
Packet Loss ◽  
Error Concealment ◽  
Experimental Results ◽  
Spatial Smoothing ◽  
Visual Effect ◽  
Matching Algorithm ◽  
Video Images ◽  
Temporal Domain ◽  
Macro Block ◽  
Multi Mode

In order to improve the decoding performance of digital satellite set-top boxes, this paper proposed a directional boundary matching algorithm on temporal domain for H.264, it considers using the spatial smoothing of video images and the movement consistency in neighbor macro-blocks to restore the damaged macro-block, with pixels matching in three directions on the boundary. On this basis, a adaptive error concealment algorithm of multi-mode is proposed, which avoids the judgment of the partition mode of damaged macro-block. Experimental results show that when in the same case of packet loss, compared with the traditional concealment algorithms, the algorithm proposed in this paper has better performance in the improvement of PSNR and visual effect.

Image Reconstruction on Quincunx Patterned Green Channel

2013 ◽  
Vol 717 ◽  
pp. 493-496
Author(s):  
Gwang Gil Jeon
Keyword(s):  
Image Reconstruction ◽  
Least Squares ◽  
Least Squares Method ◽  
Interpolation Method ◽  
Experimental Results ◽  
Color Filter ◽  
Image Artifacts ◽  
Green Channel ◽  
Filter Array ◽  
Single Sensor

This paper addresses the issue of the quincunx patterned green channel interpolation method that is obtained by single sensor cameras. Our goal is to reconstruct the green channel in Bayer color filter array (CFA) data. We present a new filter-based method for the reduction of image artifacts in green channel. To reconstruct green channel, we trained a filter using least squares method. Experimental results confirm the effectiveness of the proposed method. Compared to other bilinear and bicubic filters, the improvement in quality has been achieved.

Estimated path information gain-based robot exploration under perceptual uncertainty

Robotica ◽  
2022 ◽  
pp. 1-17
Author(s):  
Jie Liu ◽  
Chaoqun Wang ◽  
Wenzheng Chi ◽  
Guodong Chen ◽  
Lining Sun
Keyword(s):  
Decision Making ◽  
Topological Structure ◽  
Information Gain ◽  
State Of The Art ◽  
Selection Process ◽  
Random Trees ◽  
Experimental Results ◽  
Restricted Area ◽  
Structure Information ◽  
Path Information

Abstract At present, the frontier-based exploration has been one of the mainstream methods in autonomous robot exploration. Among the frontier-based algorithms, the method of searching frontiers based on rapidly exploring random trees consumes less computing resources with higher efficiency and performs well in full-perceptual scenarios. However, in the partially perceptual cases, namely when the environmental structure is beyond the perception range of robot sensors, the robot often lingers in a restricted area, and the exploration efficiency is reduced. In this article, we propose a decision-making method for robot exploration by integrating the estimated path information gain and the frontier information. The proposed method includes the topological structure information of the environment on the path to the candidate frontier in the frontier selection process, guiding the robot to select a frontier with rich environmental information to reduce perceptual uncertainty. Experiments are carried out in different environments with the state-of-the-art RRT-exploration method as a reference. Experimental results show that with the proposed strategy, the efficiency of robot exploration has been improved obviously.

scholarly journals Bivariate Hahn moments for image reconstruction

2014 ◽  
Vol 24 (2) ◽  
pp. 417-428 ◽  
Author(s):  
Haiyong Wu ◽  
Senlin Yan
Keyword(s):  
Image Reconstruction ◽  
Numerical Stability ◽  
Parameter Selection ◽  
Experimental Results ◽  
Grayscale Image ◽  
Orthogonal Moments ◽  
Binary Images ◽  
Hahn Polynomials ◽  
Discrete Orthogonal ◽  
Computational Aspects

Abstract This paper presents a new set of bivariate discrete orthogonal moments which are based on bivariate Hahn polynomials with non-separable basis. The polynomials are scaled to ensure numerical stability. Their computational aspects are discussed in detail. The principle of parameter selection is established by analyzing several plots of polynomials with different kinds of parameters. Appropriate parameters of binary images and a grayscale image are obtained through experimental results. The performance of the proposed moments in describing images is investigated through several image reconstruction experiments, including noisy and noise-free conditions. Comparisons with existing discrete orthogonal moments are also presented. The experimental results show that the proposed moments outperform slightly separable Hahn moments for higher orders.

scholarly journals CT Image Reconstruction from Sparse Projections Using Adaptive TpV Regularization

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hongliang Qi ◽  
Zijia Chen ◽  
Linghong Zhou
Keyword(s):  
Image Reconstruction ◽  
Ct Image ◽  
Minimization Method ◽  
X Ray ◽  
Structure Information ◽  
Reconstruction Methods ◽  
Projection Image ◽  
Sparse Projection ◽  
Ct Image Quality ◽  
Better Than

Radiation dose reduction without losing CT image quality has been an increasing concern. Reducing the number of X-ray projections to reconstruct CT images, which is also called sparse-projection reconstruction, can potentially avoid excessive dose delivered to patients in CT examination. To overcome the disadvantages of total variation (TV) minimization method, in this work we introduce a novel adaptive TpV regularization into sparse-projection image reconstruction and use FISTA technique to accelerate iterative convergence. The numerical experiments demonstrate that the proposed method suppresses noise and artifacts more efficiently, and preserves structure information better than other existing reconstruction methods.

AN IMPROVED EDGE-DIRECTED IMAGE INTERPOLATION ALGORITHM

2012 ◽  
Vol 12 (04) ◽  
pp. 1250023 ◽  
Author(s):  
XINGYUAN WANG ◽  
ZHIFENG CHEN ◽  
XUEMEI BAO
Keyword(s):  
Real Time ◽  
Local Structure ◽  
Time Complexity ◽  
Image Interpolation ◽  
Threshold Value ◽  
Subjective Quality ◽  
Experimental Results ◽  
Interpolation Algorithm ◽  
Visual Effects ◽  
Structure Characteristics

The paper sets forth an improved edge-directed image interpolation algorithm with low time complexity. The algorithm partitions images into homogeneous and edge areas by setting the preset threshold value based on the local structure characteristics. Specified algorithms are assigned to interpolate each classified areas respectively. The proposed method implements strategy in three steps to interpolate after setting the preset threshold value. In this way, it can achieve the goals of real-time interpolation and good subjective quality. Furthermore, the interpolated images have much more explicit edge regions and better visual effects using our proposed method than that of using other algorithms. Experimental results demonstrate that the method proposed by the authors is high-performed in image interpolation.

scholarly journals Pose Estimation of Uncooperative Unknown Space Objects from a Single Image

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaoyuan Ren ◽  
Libing Jiang ◽  
Zhuang Wang
Keyword(s):  
Pose Estimation ◽  
Experimental Results ◽  
Single Image ◽  
Space Object ◽  
Shape Model ◽  
Structure Information ◽  
Space Objects ◽  
Specific Object ◽  
Unknown Objects ◽  
Unknown Object

Estimating the 3D pose of the space object from a single image is an important but challenging work. Most of the existing methods estimate the 3D pose of known space objects and assume that the detailed geometry of a specific object is known. These methods are not available for unknown objects without the known geometry of the object. In contrast to previous works, this paper devotes to estimate the 3D pose of the unknown space object from a single image. Our method estimates not only the pose but also the shape of the unknown object from a single image. In this paper, a hierarchical shape model is proposed to represent the prior structure information of typical space objects. On this basis, the parameters of the pose and shape are estimated simultaneously for unknown space objects. Experimental results demonstrate the effectiveness of our method to estimate the 3D pose and infer the geometry of unknown typical space objects from a single image. Moreover, experimental results show the advantage of our approach over the methods relying on the known geometry of the object.

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