Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description

2018 ◽  
Vol 27 (1) ◽  
pp. 394-405 ◽  
Author(s):  
Ke Gu ◽  
Vinit Jakhetiya ◽  
Jun-Fei Qiao ◽  
Xiaoli Li ◽  
Weisi Lin ◽  
...  
Keyword(s):  
Image Description ◽  
Quality Metric ◽  
Model Based ◽  
Local Image

AN ADAPTIVE THRESHOLDING-BASED COLOR REDUCTION ALGORITHM AND ITS APPLICATIONS

2011 ◽  
Vol 11 (01) ◽  
pp. 83-101
Author(s):  
P. S. PERIASAMY ◽  
S. ATHINARAYANAN ◽  
K. DURAISWAMY
Keyword(s):  
State Of The Art ◽  
Adaptive Thresholding ◽  
Large Set ◽  
Reduction Algorithm ◽  
Image Description ◽  
Multiple Images ◽  
Color Reduction ◽  
Quality Metric ◽  
Reduction Methods ◽  
Digital Broadcasting

In this paper, we present a novel adaptive thresholding-based color reduction algorithm. The proposed algorithm supports creation of a common palette for multiple images and transparent alpha images. This method was extensively tested for a large set of images and the results are reported here. The applications of proposed algorithm like qualitative image description, digital broadcasting, and bandwidth reduction are discussed in detail. The quality metric values of the experimental results show that the proposed method produces excellent results and outperforms existing state-of-the-art color reduction methods.

A New Regularization Model Based on Non-Local Means for Image Deblurring

2013 ◽  
Vol 411-414 ◽  
pp. 1164-1169 ◽  
Author(s):  
Zhi Ming Wang ◽  
Hong Bao
Keyword(s):  
Image Denoising ◽  
Processing Speed ◽  
Operator Splitting ◽  
Image Deblurring ◽  
Local Similarity ◽  
Model Based ◽  
Local Means ◽  
Ill Posed ◽  
Non Local ◽  
Local Image

Image deblurring with noise is a typical ill-posed problem needs regularization. Various regularization models were proposed during several decades study, such as Tikhonov and TV. A new regularization model based non-local similarity constrains is proposed in this paper, which used l2 non-local norms and could be easily solved by fast non-local image denoising algorithm. By combining with Bregmanrized operator splitting (BOS) algorithm, a fast and efficient iterative three step image deblurring scheme is given. Experimental results show that proposed regularization model obtained better results on ten common test images than other similar regularization model including newly proposed NLTV regularization, both in deblurring performance (PSNR and MSSIM) and processing speed.

scholarly journals Compact Local Directional Texture Pattern for Local Image Description

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Hui Zeng ◽  
Rui Zhang ◽  
Mingming Huang ◽  
Xiuqing Wang
Keyword(s):  
Image Matching ◽  
Local Region ◽  
Image Feature ◽  
Image Description ◽  
Texture Pattern ◽  
Gradient Magnitude ◽  
Gradient Orientation ◽  
Contrast Information ◽  
Directional Texture ◽  
Local Image

This paper presents an effective local image feature region descriptor, called CLDTP descriptor (Compact Local Directional Texture Pattern), and its application in image matching and object recognition. The CLDTP descriptor encodes the directional and contrast information in a local region, so it contains the gradient orientation information and the gradient magnitude information. As the dimension of the CLDTP histogram is much lower than the dimension of the LDTP histogram, the CLDTP descriptor has higher computational efficiency and it is suitable for image matching. Extensive experiments have validated the effectiveness of the designed CLDTP descriptor.

scholarly journals Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

2018 ◽  
Vol 27 (4) ◽  
pp. 1994-2007 ◽  
Author(s):  
Martin Kiechle ◽  
Martin Storath ◽  
Andreas Weinmann ◽  
Martin Kleinsteuber
Keyword(s):  
Texture Segmentation ◽  
Image Features ◽  
Model Based ◽  
Local Image ◽  
Local Image Features
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