Image optimization method of large autostereoscopic display of dual projection types

2019 ◽  
Author(s):  
Yuta Kuroda ◽  
Isao Nishihara ◽  
Takayuki Nakata
Keyword(s):  
Optimization Method ◽  
Autostereoscopic Display ◽  
Image Optimization ◽  
Dual Projection

Novel Image Optimization Method for Joint Photoacoustic Tomography

2014 ◽  
Vol 31 (5) ◽  
pp. 054302 ◽  
Author(s):  
Wen-Chao Li ◽  
Jie Yuan ◽  
Qing-Hong Shen ◽  
Yao Yu ◽  
Yu Zhou ◽  
...  
Keyword(s):  
Optimization Method ◽  
Photoacoustic Tomography ◽  
Image Optimization

scholarly journals Biomedical Photoacoustic Imaging Optimization with Deconvolution and EMD Reconstruction

2018 ◽  
Vol 8 (11) ◽  
pp. 2113 ◽  
Author(s):  
Chengwen Guo ◽  
Yingna Chen ◽  
Jie Yuan ◽  
Yunhao Zhu ◽  
Qian Cheng ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Empirical Mode Decomposition ◽  
Photoacoustic Imaging ◽  
Optimization Method ◽  
Positive Polarity ◽  
Image Optimization ◽  
Mode Decomposition ◽  
Phantom Studies ◽  
Micro Structures

A photoacoustic (PA) signal of an ideal optical absorbing particle is a single N-shape wave. PA signals are a combination of several individual N-shape waves. However, the N-shape wave basis leads to aliasing between adjacent micro-structures, which deteriorates the quality of final PA images. In this paper, we propose an image optimization method by processing raw PA signals with deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent deconvolution kernel, which is measured in advance. EMD is subsequently adopted to further process the PA signals adaptively with two restrictive conditions: positive polarity and spectrum consistency. With this method, signal aliasing is alleviated, and the micro-structures and detail information, previously buried in the reconstructing images, can now be revealed. To validate our proposed method, numerical simulations and phantom studies are implemented, and reconstructed images are used for illustration.

scholarly journals A training image optimization method in multiple-point geostatistics and its application in geological modeling

2019 ◽  
Vol 46 (4) ◽  
pp. 739-745
Author(s):  
Lixin WANG ◽  
Yanshu YIN ◽  
Wenjie FENG ◽  
Taizhong DUAN ◽  
Lei ZHAO ◽  
...  
Keyword(s):  
Optimization Method ◽  
Training Image ◽  
Multiple Point ◽  
Geological Modeling ◽  
Image Optimization

Research on Face Image Optimization Method Based on Face Clustering in Video

2019 ◽  
Vol 56 (20) ◽  
pp. 201002
Author(s):  
王畅 Wang Chang ◽  
崔荣一 Cui Rongyi ◽  
金璟璇 Jin Jingxuan ◽  
金小峰 Jin Xiaofeng
Keyword(s):  
Optimization Method ◽  
Face Image ◽  
Face Clustering ◽  
Image Optimization

scholarly journals A Spatial-Frequency Domain Associated Image-Optimization Method for Illumination-Robust Image Matching

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6489
Author(s):  
Chun Liu ◽  
Shoujun Jia ◽  
Hangbin Wu ◽  
Doudou Zeng ◽  
Fanjin Cheng ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Frequency Domain ◽  
Image Matching ◽  
Optimization Method ◽  
Frequency Domain Analysis ◽  
Image Features ◽  
Practical Applications ◽  
Feature Enhancement ◽  
Image Optimization ◽  
Spatial Frequency Domain

Image matching forms an essential means of data association for computer vision, photogrammetry and remote sensing. The quality of image matching is heavily dependent on image details and naturalness. However, complex illuminations, denoting extreme and changing illuminations, are inevitable in real scenarios, and seriously deteriorate image matching performance due to their significant influence on the image naturalness and details. In this paper, a spatial-frequency domain associated image-optimization method, comprising two main models, is specially designed for improving image matching with complex illuminations. First, an adaptive luminance equalization is implemented in the spatial domain to reduce radiometric variations, instead of removing all illumination components. Second, a frequency domain analysis-based feature-enhancement model is proposed to enhance image features while preserving image naturalness and restraining over-enhancement. The proposed method associates the advantages of the spatial and frequency domain analyses to complete illumination equalization, feature enhancement and naturalness preservation, and thus acquiring the optimized images that are robust to the complex illuminations. More importantly, our method is generic and can be embedded in most image-matching schemes to improve image matching. The proposed method was evaluated on two different datasets and compared with four other state-of-the-art methods. The experimental results indicate that the proposed method outperforms other methods under complex illuminations, in both matching performances and practical applications such as structure from motion and multi-view stereo.

Image Optimization Algorithm Based on Salient Region and Layout Adjustment

2010 ◽  
Vol 40-41 ◽  
pp. 577-583
Author(s):  
Zhen Hua ◽  
Ye Wei Li ◽  
Jin Jiang Li
Keyword(s):  
Visual Attention ◽  
Optimization Algorithm ◽  
Optimization Method ◽  
Attention Model ◽  
Salient Region ◽  
Advantages And Disadvantages ◽  
Image Optimization ◽  
Optimization Function ◽  
Salient Regions

The purpose of image optimization is that the salient region of image is stand out, and is layout an image met the demand. The existed image optimization method is summarized, and their advantages and disadvantages respectively analyzed. The improved visual attention model is described, and is used to detect the salient region of image. The parameters of image optimization are calculated by the optimization function of image layout rules. At last, the weights of the images optimized parameters are adjusted by the image layout and adjustment function based on image optimized parameters, to achieve image layout and obtain the most optimal image, to realize image optimization. Experimental results validate that this methods not only achieve image optimization, but also accurately and automatically achieve to shorten distance and enlarge salient regions, improve the quality of the image optimization, and has good robustness.

Scanning Tunneling Microscopy of Amorphous Carbon Films

1990 ◽  
Vol 48 (1) ◽  
pp. 318-319
Author(s):  
Mircea Fotino ◽  
D.C. Parks
Keyword(s):  
Scanning Tunneling Microscopy ◽  
Amorphous Carbon ◽  
Carbon Films ◽  
Atomic Scale ◽  
Scanning Tunneling ◽  
Tunneling Microscopy ◽  
Amorphous Carbon Films ◽  
Image Optimization ◽  
Step Procedure ◽  
Stm Images

In the last few years scanning tunneling microscopy (STM) has made it possible and easily accessible to visualize surfaces of conducting specimens at the atomic scale. Such performance allows the detailed characterization of surface morphology in an increasing spectrum of applications in a wide variety of fields. Because the basic imaging process in STM differs fundamentally from its equivalent in other well-established microscopies, good understanding of the imaging mechanism in STM enables one to grasp the correct information content in STM images. It thus appears appropriate to explore by STM the structure of amorphous carbon films because they are used in many applications, in particular in the investigation of delicate biological specimens that may be altered through the preparation procedures.All STM images in the present study were obtained with the commercial instrument Nanoscope II (Digital Instruments, Inc., Santa Barbara, California). Since the importance of the scanning tip for image optimization and artifact reduction cannot be sufficiently emphasized, as stressed by early analyses of STM image formation, great attention has been directed toward adopting the most satisfactory tip geometry. The tips used here consisted either of mechanically sheared Pt/Ir wire (90:10, 0.010" diameter) or of etched W wire (0.030" diameter). The latter were eventually preferred after a two-step procedure for etching in NaOH was found to produce routinely tips with one or more short whiskers that are essentially rigid, uniform and sharp (Fig. 1) . Under these circumstances, atomic-resolution images of cleaved highly-ordered pyro-lytic graphite (HOPG) were reproducibly and readily attained as a standard criterion for easily recognizable and satisfactory performance (Fig. 2).

A dual projection model of partisan attitude perceptions

2014 ◽  
Author(s):  
Jessica Keating ◽  
Leaf Van Boven ◽  
Charles Judd
Keyword(s):  
Projection Model ◽  
Dual Projection
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