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On the extraction and representation of land cover information derived from remotely sensed imageryManslow, John January 2001 (has links)
No description available.
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Fiabilité et précision en stéréoscopie : application à l'imagerie aérienne et satellitaire à haute résolutionSabater, Neus 07 December 2009 (has links) (PDF)
Cette thèse se situe dans le cadre du projet MISS (Mathématiques de l'Imagerie Stéréoscopique Spatiale) monté par le CNES en collaboration avec plusieurs laboratoires universitaires en 2007. Ce projet se donne l'objectif ambitieux de modéliser un satellite stéréoscopique, prenant deux vues non simultanées mais très rapprochées de la Terre en milieu urbain. Son but principal est d'obtenir une chaîne automatique de reconstruction urbaine à haute résolution à partir de ces deux vues. Ce projet se heurte toutefois à des problèmes de fond que la présente thèse s'attache à résoudre. Le premier problème est le rejet des matches qui pourraient se produire par hasard, notamment dans les zones d'ombres ou d'occlusion, et le rejet également des mouvements au sol (véhicules, piétons, etc.). La thèse propose une méthode de rejet de faux matches basée sur la méthodologie dite a contrario. On montre la consistance mathématique de cette méthode de rejet, et elle est validée sur des paires simulées exactes, sur des vérités terrain fournies par le CNES, et sur des paires classiques de benchmark (Middlebury). Les matches fiables restants représentent entre 40% et 90% des pixels selon les paires testées. Le second problème de fond abordé est la précision. En effet le type de stéréoscopie envisagé exige un très faible angle entre les deux vues, qui sont visuellement presque identiques. Pour obtenir un relief correct, il faut effectuer un recalage extrêmement précis, et calibrer le niveau de bruit qui permet un tel recalage. La thèse met en place une méthode de recalage subpixélien, qui sera démontrée être optimale par des arguments mathématiques et expérimentaux. Ces résultats étendent et améliorent les résultats obtenus au CNES par la méthode MARC. En particulier, il sera montré sur les images de benchmark Middlebury que la précision théorique permise par le bruit correspond bien à celle obtenue sur les matches fiables. Bien que ces résultats soient obtenus dans le cadre d'un dispositif d'acquisition précis (stéréoscopie aérienne ou satellitaire à faible angle), tous les résultats sont utilisables en stéréoscopie quelconque, comme montré dans beaucoup d'expériences.
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[en] MOTION ESTIMATION METHOD WITH SUBPIXEL RESOLUTION OF CODEC H264/AVC / [pt] MÉTODOS DE ESTIMAÇÃO DE MOVIMENTO COM RESOLUÇÃO EM SUBPIXEL NO CODEC H264/AVCJULIANO MELQUIADES VIANELLO 23 July 2007 (has links)
[pt] Foi desenvolvido pelos grupos MPEG (Moving Picture Expert
Group) e
VCEG (Video Coding Expert Group) um novo padrão de
codificação de vídeo
denominado AVC (Advanced Vídeo Coding). Este padrão
fornece uma
capacidade de compressão maior de vídeo se comparado com
os padrões
anteriores. A estimação de movimento é a fase da
codificação de vídeo que
demanda maior tempo de processamento. Estimação de
movimento é
computacionalmente custosa para H.264/AVC se o método Full
Search [1] é
usado. A fim de reduzir o tempo de codificação, o software
de referência JM 9.8
adota um rápido método de estimação de movimento para
pixel inteiro chamado
UMHexagonS e um método para pixel fracionário chamado
CBFPS. Um método
proposto por Xiaoquan Yi, Jun Zhang, Nam Ling e Weijia
Shang [2] chamado
aqui, por simplicidade, de P021 apresenta, em comparação
com o software de
referência JM, uma melhor e simplificada forma de
estimação de movimento
para aumentar a velocidade do processo de codificação e
manter a qualidade
visual do vídeo. Visando diminuir ainda mais o tempo de
processamento e o
custo computacional apresentada pelos métodos citados
anteriormente, o que é
necessário principalmente para aplicações de codificação
de vídeo móveis, como
celulares e palm tops e aplicações de tempo real, como
videoconferência, este
trabalho propõe um método de estimação de movimento que
consiste em evitar o
processamento de blocos que não se beneficiam da pesquisa
de metade de pixel.
Após a execução dos testes, pode-se constatar que com uma
qualidade de vídeo
semelhante, o método proposto reduz o tempo de
processamento em 76,17%,
75,95% e 11,74% em média quando comparado com os métodos
Full Search,
JM 98 e P021. Além disso, este método praticamente
preserva a taxa de bits,
apresentando um pequeno aumento de 8,72% , 8,06% e 8,02%
em média quando
comparado com os mesmos métodos. Isto representa, em nossa
opinião, um
pequeno preço a ser pago, considerando os benefícios em
termos de tempo de
processamento. / [en] The MPEG (Moving Picture Experts Group) and the VCEG (Video
Coding Experts Group) have developed a new video
compression standard
entitled AVC (Advanced Video Coding). This standard offers
the capacity of
video compression greater than the previous standards.The
motion estimation
which is a phase of the video compression is extremely
computer-intensive and
therefore demands most of the processing time. When Full
Search [1] method is
used for H.264/AVC, this process is extremely expensive.
In order to reduce
encoding time, the reference software JM (throughout this
work, JM98 is the
version used) has respectively adopted a fast motion
estimation method for the
integer pixel called UMHexagonS and a method for the sub-
pixel called CBFPS.
A method proposed by Xiaoquan Yi, Jun Zhang, Nam Ling e
Weijia Shang [2]
called here P021 (as referenced by the Joint Video Team)
has shown, when
compared to the reference software JM, a simple way of
motion estimation that
increases the speed of coding process while maintaining
the video visual quality.
In order to decrease the processing time and computational
cost of these
methods, which are: i) particularly needed in mobile video
coding applications
such as mobile phones and palmtops; ii) in real time
applications such as
videoconference, this work proposes a motion estimation
method that eliminates
the processing of blocks that does not produce benefits
for the half-pixel search.
The simulation results show that the proposed method
reduces the processing
time in 76,17%, 75,95% and 11,74% in average when
respectively compared
with Full Search, JM98 and P021 methods, without relevant
impact in video
quality. Besides, this method produces a bits rate
increase of 8,72% , 8,06% e
8,02% in average when compared with the same methods. This
is in our opinion,
an inexpensive price to be paid when the time benefits are
considered.
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Robust Real-Time Estimation of Region Displacements in Video SequencesSkoglund, Johan January 2007 (has links)
<p>The possibility to use real-time computer vision in video sequences gives many opportunities for a system to interact with the environment. Possible ways for interaction are e.g. augmented reality like in the MATRIS project where the purpose is to add new objects into the video sequence, or surveillance where the purpose is to find abnormal events.</p><p>The increase of the speed of computers the last years has simplified this process and it is now possible to use at least some of the more advanced computer vision algorithms that are available. The computational speed of computers is however still a problem, for an efficient real-time system efficient code and methods are necessary. This thesis deals with both problems, one part is about efficient implementations using single instruction multiple data (SIMD) instructions and one part is about robust tracking.</p><p>An efficient real-time system requires efficient implementations of the used computer vision methods. Efficient implementations requires knowledge about the CPU and the possibilities given. In this thesis, one method called SIMD is explained. SIMD is useful when the same operation is applied to multiple data which usually is the case in computer vision, the same operation is executed on each pixel.</p><p>Following the position of a feature or object in a video sequence is called tracking. Tracking can be used for a number of applications. The application in this thesis is to use tracking for pose estimation. One way to do tracking is to cut out a small region around the feature, creating a patch and find the position on this patch in the other frames. To find the position, a measure of the difference between the patch and the image in a given position is used. This thesis thoroughly investigates the sum of absolute difference (SAD) error measure. The investigation involves different ways to improve the robustness and to decrease the average error. One method to estimate the average error, the covariance of the position error is proposed. An estimate of the average error is needed when different measurements are combined.</p><p>Finally, a system for camera pose estimation is presented. The computer vision part of this system is based on the result in this thesis. This presentation contains also a discussion about the result of this system.</p> / Report code: LIU-TEK-LIC-2007:5. The report code in the thesis is incorrect.
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Fractional Snow-Cover Mapping Through Artificial Neural Network Analysis of MODIS Surface Reflectance.Dobreva, Iliyana D. 2009 December 1900 (has links)
Accurate areal measurements of snow-cover extent are important for hydrological and climate modeling. The traditional method of mapping snow cover is binary where a pixel is approximated to either snow-covered or snow-free. Fractional snow cover (FSC) mapping achieves a more precise estimate of areal snow-cover extent by determining the fraction of a pixel that is snow-covered. The two most common FSC methods using Moderate Resolution Imaging Spectroradiometer (MODIS) images are linear spectral unmixing and the empirical Normalized Difference Snow Index (NDSI) method. Machine learning is an alternative to these approaches for estimating FSC, as Artificial Neural Networks (ANNs) have been used for estimating the subpixel abundances of other surfaces. The advantages of ANNs over the other approaches are that they can easily incorporate auxiliary information such as land-cover type and are capable of learning nonlinear relationships between surface reflectance and snow fraction. ANNs are especially applicable to mapping snow-cover extent in forested areas where spatial mixing of surface components is nonlinear.
This study developed an ANN approach to snow-fraction mapping. A feed-forward ANN was trained with backpropagation to estimate FSC from MODIS surface reflectance, NDSI, Normalized Difference Vegetation Index (NDVI) and land cover as inputs. The ANN was trained and validated with high spatial-resolution FSC derived from Landsat Enhanced Thematic Mapper Plus (ETM+) binary snow-cover maps.
ANN achieved best result in terms of extent of snow-covered area over evergreen forests, where the extent of snow cover was slightly overestimated. Scatter plot graphs of the ANN and reference FSC showed that the neural network tended to underestimate snow fraction in high FSC and overestimate it in low FSC. The developed ANN compared favorably to the standard MODIS FSC product with the two methods estimating the same amount of total snow-covered area in the test scenes.
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Using Subpixel Technology in Contour Recognition on Low-resolution Hexagonal ImagesLee, Yorker 08 June 2000 (has links)
Pattern recognition is very important in automatic industry. The automation machinery vision system must exchange information very fast with the object we need. So the machinery vision system must have powerful recognition ability.
There are more important on image processing, lately. But most researches of image processing are developed on high-resolution image. However, in same situation, for increasing the processing speed, reducing the saving space.
Low-resolution image are the only way to achieve the above condition up to now. For the purpose of quickly recognition, we construct the recognition system on low-resolution image.
From observing the characteristic of hexagonal grid, we knew the hexagonal grid have greater angular resolution and better image performance than rectangular grid. Therefore, we apply the hexagonal grid on low-resolution image, and using Curve Bend Function (call CBF) on hexagonal gird system; for promoting the accuracy of recognition.We presented an technique of subpixel on low-resolution hexagonal image to obtain better results.
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Optimal sub pixel arrangements and coding for ultra-high resolution three-dimensional OLED displaysYordanov, Zhivko. Unknown Date (has links) (PDF)
Kassel, University, Diss., 2007.
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Zeitliche Konturgraphverfolgung /Kellner, Michael. January 2007 (has links)
Zugl.: Passau, University, Diss., 2007.
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Optimization of Sampling Structure Conversion Methods for Color Mosaic DisplaysZheng, Xiang January 2014 (has links)
Although many devices can be used to capture images of high resolution, there is still a need to show these images on displays with low resolution. Existing methods of subpixel-based down-sampling are reviewed in this thesis and their limitations are described. A new approach to optimizing sampling structure conversion for color mosaic displays is developed. Full color images are filtered by a set of optimal filters before down-sampling, resulting in better image quality according to the SCIELAB measure, a spatial extension of the CIELAB metric measuring perceptual color difference. The typical RGB stripe display pattern is tested to get the optimal filters using least-squares filter design. The new approach is also implemented on a widely used two-dimensional display pattern, the Pentile RGBG. Clear images are produced and color fringing artifacts are reduced. Quality of down-sampled images are compared using SCIELAB and by visual inspection.
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Linear Unmixing of Hyperspectral Signals via Wavelet Feature ExtractionLi, Jiang 13 December 2002 (has links)
A pixel in remotely sensed hyperspectral imagery is typically a mixture of multiple electromagnetic radiances from various ground cover materials. Spectral unmixing is a quantitative analysis procedure used to recognize constituent ground cover materials (or endmembers) and obtain their mixing proportions (or abundances) from a mixed pixel. The abundances are typically estimated using the least squares estimation (LSE) method based on the linear mixture model (LMM). This dissertation provides a complete investigation on how the use of appropriate features can improve the LSE of endmember abundances using remotely sensed hyperspectral signals. The dissertation shows how features based on signal classification approaches, such as discrete wavelet transform (DWT), outperform features based on conventional signal representation methods for dimensionality reduction, such as principal component analysis (PCA), for the LSE of endmember abundances. Both experimental and theoretical analyses are reported in the dissertation. A DWT-based linear unmixing system is designed specially for the abundance estimation. The system utilizes the DWT as a pre-processing step for the feature extraction. Based on DWT-based features, the system utilizes the constrained LSE for the abundance estimation. Experimental results show that the use of DWT-based features reduces the abundance estimation deviation by 30-50% on average, as compared to the use of original hyperspectral signals or conventional PCA-based features. Based on the LMM and the LSE method, a series of theoretical analyses are derived to reveal the fundamental reasons why the use of the appropriate features, such as DWT-based features, can improve the LSE of endmember abundances. Under reasonable assumptions, the dissertation derives a generalized mathematical relationship between the abundance estimation error and the endmember separabilty. It is proven that the abundance estimation error can be reduced through increasing the endmember separability. The use of DWT-based features provides a potential to increase the endmember separability, and consequently improves the LSE of endmember abundances. The stability of the LSE of endmember abundances is also analyzed using the concept of the condition number. Analysis results show that the use of DWT-based features not only improves the LSE of endmember abundances, but also improves the LSE stability.
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