Imaging Indoor Tracer-Gas Concentrations with Computed Tomography: Experimental Results with a Remote Sensing FTIR System

AIHAJ ◽  
1994 ◽  
Vol 55 (5) ◽  
pp. 395-402 ◽  
Author(s):  
M.G. Yost ◽  
A.J. Gadgil ◽  
A.C. Drescher ◽  
Y. Zhou ◽  
M.A. Simonds ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Remote Sensing ◽  
Experimental Results ◽  
Tracer Gas

Stationary and time-dependent indoor tracer-gas concentration profiles measured by OP-FTIR remote sensing and SBFM-computed tomography

1997 ◽  
Vol 31 (5) ◽  
pp. 727-740 ◽  
Author(s):  
A.C. Drescher ◽  
D.Y. Park ◽  
M.G. Yost ◽  
A.J. Gadgil ◽  
S.P. Levine ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Remote Sensing ◽  
Time Dependent ◽  
Concentration Profiles ◽  
Tracer Gas ◽  
Gas Concentration

Lossless Compression for Text and Images

1997 ◽  
Vol 08 (01) ◽  
pp. 179-231 ◽  
Author(s):  
Alistair Moffat ◽  
Timothy C. Bell ◽  
Ian H. Witten
Keyword(s):  
Remote Sensing ◽  
Lossless Compression ◽  
Lossy Compression ◽  
International Standards ◽  
Experimental Results ◽  
Extensive Discussion ◽  
Standard Methods ◽  
Sensing Applications ◽  
Other Information ◽  
Remote Sensing Applications

Most data that is inherently discrete needs to be compressed in such a way that it can be recovered exactly, without any loss. Examples include text of all kinds, experimental results, and statistical databases. Other forms of data may need to be stored exactly, such as images—particularly bilevel ones, or ones arising in medical and remote-sensing applications, or ones that may be required to be certified true for legal reasons. Moreover, during the process of lossy compression, many occasions for lossless compression of coefficients or other information arise. This paper surveys techniques for lossless compression. The process of compression can be broken down into modeling and coding. We provide an extensive discussion of coding techniques, and then introduce methods of modeling that are appropriate for text and images. Standard methods used in popular utilities (in the case of text) and international standards (in the case of images) are described.

Design and Implementation of Spurs Detection System Based on OpenCV

2011 ◽  
Vol 345 ◽  
pp. 217-222
Author(s):  
Peng He ◽  
Lian Peng Wang ◽  
Na Wang ◽  
Gang Xu
Keyword(s):  
Computed Tomography ◽  
Embedded System ◽  
Detection System ◽  
Experimental Results ◽  
Design And Implementation ◽  
Function Expansion ◽  
The Embedded System ◽  
Improved Function ◽  
Small Bone ◽  
Improved Algorithm

In order to better solve the problem of detection of small bone spurs with convenient and accurate way, a portable spur detection system is designed. This system, in view of spur reproducibility characteristic, is characterized by the application for a kind of the improved algorithm based on the OpenCV. And it was successfully transplanted into the embedded system. The experimental results indicated that this system might precisely examine the small spur with difficulty discovery by naked eyes used fully by two images of computed tomography which done in different periods. The spur detection system needs to be further improved function to realize more applications. In fact, function expansion based on the system is easy to realize.

Segmentation of Kidneys from Computed Tomography Using 3D Fast GrowCut Algorithm

2013 ◽  
Vol 333-335 ◽  
pp. 1145-1150 ◽  
Author(s):  
Gao Yuan Dai ◽  
Zhi Cheng Li ◽  
Jia Gu ◽  
Lei Wang ◽  
Xing Min Li ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
Experimental Results ◽  
Volume Data ◽  
Great Role ◽  
Color Features ◽  
Monotonically Decreasing Function ◽  
Kidney Segmentation ◽  
Ct Volume

This paper proposes a fast GrowCut (FGC) algorithm and applies the new algorithm in three-dimensional (3D)kidney segmentation from computed tomography (CT) volume data. Users could mark the object of interest with different labels in CT slices.FGC propagates the labels using monotonically decreasing function and color features to derive an optimal cut for a given data in space. The color features play a great role in comparing with neighborhood cells. The experimental results clearly demonstrate the superiority of FGC in accuracy and speed.

Laser long-range remote-sensing program experimental results

1995 ◽  
Author(s):  
Ronald G. Highland ◽  
Michael L. Shilko, Sr. ◽  
Marsha J. Fox ◽  
John D. Gonglewski ◽  
Stanley R. Czyzak ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Long Range ◽  
Experimental Results

scholarly journals Approximate Sparse Regularized Hyperspectral Unmixing

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Chengzhi Deng ◽  
Yaning Zhang ◽  
Shengqian Wang ◽  
Shaoquan Zhang ◽  
Wei Tian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Optimization Model ◽  
Optimization Problem ◽  
Augmented Lagrangian ◽  
Hyperspectral Image ◽  
State Of The Art ◽  
Experimental Results ◽  
Hyperspectral Images ◽  
Hyperspectral Unmixing ◽  
Variable Splitting

Sparse regression based unmixing has been recently proposed to estimate the abundance of materials present in hyperspectral image pixel. In this paper, a novel sparse unmixing optimization model based on approximate sparsity, namely, approximate sparse unmixing (ASU), is firstly proposed to perform the unmixing task for hyperspectral remote sensing imagery. And then, a variable splitting and augmented Lagrangian algorithm is introduced to tackle the optimization problem. In ASU, approximate sparsity is used as a regularizer for sparse unmixing, which is sparser thanl1regularizer and much easier to be solved thanl0regularizer. Three simulated and one real hyperspectral images were used to evaluate the performance of the proposed algorithm in comparison tol1regularizer. Experimental results demonstrate that the proposed algorithm is more effective and accurate for hyperspectral unmixing than state-of-the-artl1regularizer.

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