A two-stage scheme for lossless compression of images

Author(s):  
G. Mandyam ◽  
N. Ahmed ◽  
S.D. Stearns
Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 412
Author(s):  
Mingqiang Guo ◽  
Zhenzhen Song ◽  
Chengde Han ◽  
Saishang Zhong ◽  
Ruina Lv ◽  
...  

In this paper, we propose a novel guided normal filtering followed by vertex updating for mesh denoising. We introduce a two-stage scheme to construct adaptive consistent neighborhoods for guided normal filtering. In the first stage, we newly design a consistency measurement to select a coarse consistent neighborhood for each face in a patch-shift manner. In this step, the selected consistent neighborhoods may still contain some features. Then, a graph-cut based scheme is iteratively performed for constructing different adaptive neighborhoods to match the corresponding local shapes of the mesh. The constructed local neighborhoods in this step, known as the adaptive consistent neighborhoods, can avoid containing any geometric features. By using the constructed adaptive consistent neighborhoods, we compute a more accurate guide normal field to match the underlying surface, which will improve the results of the guide normal filtering. With the help of the adaptive consistent neighborhoods, our guided normal filtering can preserve geometric features well, and is robust against complex shapes of surfaces. Intensive experiments on various meshes show the superiority of our method visually and quantitatively.


1970 ◽  
Vol 6 (9) ◽  
pp. 704-706
Author(s):  
A. P. Dorokhov ◽  
G. V. Emel'yanova ◽  
I. I. Ioffe ◽  
N. P. Mel'nikova ◽  
V. E. Shefter

2012 ◽  
Vol 452-453 ◽  
pp. 369-373 ◽  
Author(s):  
Rong Chang Chen ◽  
Pei Hsuan Shang ◽  
Mei Chun Chen

In this paper we employ a two-stage approach to solve the project reviewer assignment problem. The objective is to best satisfy the preferences of reviewers. In addition, the number of total movement times of reviewers is minimized. Reviewers are first invited to show their preferences to the projects with a number to indicate their priority. After aggregating the data, a two-stage approach is used to best match the reviewers and projects. At the first stage reviewers are assigned, while at the second stage review venues are arranged in a way that the total change times of venues for reviewers are minimized. The results show that the proposed two-stage scheme is very helpful in solving the project reviewer assignment problem.


2021 ◽  
Vol 16 (3) ◽  
pp. 1139-1194
Author(s):  
Yunan Li

A principal distributes an indivisible good to budget‐constrained agents when both valuation and budget are agents' private information. The principal can verify an agent's budget at a cost. The welfare‐maximizing mechanism can be implemented via a two‐stage scheme. First, agents report their budgets, receive cash transfers, and decide whether to enter a lottery over the good. Second, recipients of the good can sell it on a resale market but must pay a sales tax. Low‐budget agents receive a higher cash transfer, pay a lower price to enter the lottery, and face a higher sales tax. They are also randomly inspected.


Author(s):  
Bader S Alanazi

In this paper, we compare two-stage sequential sampling scheme with fully sequential sampling scheme to test software and estimate reliability. In two-stage sampling scheme, test cases can be allocated among partitions in two phases. Our goal of this scheme is to obtain the near-optimal choices for distributing of test cases among sub-domains by minimizing the variance of the overall software reliability estimator. The two-stage sampling scheme is expected to be more convenient than a fully sequential sampling scheme because it requires fewer computations than the fully sequential sampling scheme. Also, the two-stage sampling scheme is expected to perform better than a balanced sampling scheme by virtue of lower the variance incurred by the overall estimated software reliability


2013 ◽  
Vol 290 ◽  
pp. 19-27 ◽  
Author(s):  
Jiaji Wu ◽  
Chong Liang ◽  
Jianxiang Han ◽  
Zejun Hu ◽  
Dehong Huang ◽  
...  

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