Many computer vision and imageprocessingalgorithms rely on the knowledge of the image noise variance as their input. parameter. However, in practice, the distinction between noise and image features is not easy to d...
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ISBN:
(纸本)0819452017
Many computer vision and imageprocessingalgorithms rely on the knowledge of the image noise variance as their input. parameter. However, in practice, the distinction between noise and image features is not easy to draw. In this paper, image noise variance is estimated by a novel method employing rigorously derived polynomial masks. The method is based on the assumption that the image can be locally represented as a polynomial of the given degree and constitutes a generalization of some of previously proposed approaches.
Cloud-based data processing latency mainly depends on the transmission delay of data to the cloud and the used data processing algorithm. To minimize the transmission delay, it is important to compress the transferred...
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ISBN:
(纸本)9798350399462
Cloud-based data processing latency mainly depends on the transmission delay of data to the cloud and the used data processing algorithm. To minimize the transmission delay, it is important to compress the transferred data without reducing the quality of the data. When using data compression algorithms, it is important to validate the impact of these algorithms on the detection quality. This work evaluates the effects of image compression and transmission over wireless interfaces on state of the art neural networks. Therefore, a modern imageprocessing platform for next generation automotive processing architectures, as used in software defined vehicles, is introduced. The impacts of different image encoders as well as data transmission parameters are investigated and discussed.
Efficient imageprocessing can lead to complex algorithms. In resources are limited and the approach of linear algorithm does not allow to decrease complexity regarding the variations of these resources availability. ...
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Efficient imageprocessing can lead to complex algorithms. In resources are limited and the approach of linear algorithm does not allow to decrease complexity regarding the variations of these resources availability. Agents are autonomous entities brought together into systems. They interact between them and with their environment to perform tasks. interactions allow them to share knowledge and capacities in order to adapt themselves to a changing context. In this paper we propose to use Multi-agents systemsalgorithms to perform flexible imageprocessing in an Embedded context. We will introduce our hardware context and the architecture choices made to adapt Multi -agents systems to the Embedded field. We will then present an experiment focusing on pixel interpolation process to study the flexibility of our solution. (C) 2016, IFAC (International Fedaration of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
This paper focuses on the fast texture and structure reconstruction of images. The proposed method, applied to images, consists of several steps. The first one deals with the extracted textural features of the input i...
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ISBN:
(纸本)9780819494283
This paper focuses on the fast texture and structure reconstruction of images. The proposed method, applied to images, consists of several steps. The first one deals with the extracted textural features of the input images based on the Law's energy. The pixels around damaged image regions are clustered using these features, that allow to define the correspondence between pixels from different patches. Second, cubic spline curve is applied to reconstruct a structure and to connect edges and contours in the damaged area. The choice of the current pixel to be recovered is decided using the fast marching approach The Telea method or modifications of the exemplar based method are used after this depending on the classification of the regions where to-be-restored pixel is located. In modification to quickly find patches we use the perceptual hash. Such a strategy allows to get some data structure containing the hashes of similar patches. This enables us to reduce the search procedure to the procedure for "calculations" of the patch The proposed method is tested on various samples of images, with different geometrical features and compared with the state-of-the-art image inpainting methods;the proposed technique is shown to produce better results in reconstruction of missing small and large objects on test images.
Extracting a human silhouette from an image is the enabling step for many high-level vision processing tasks, such as human tracking and activity analysis. Although there are a number of silhouette extraction and huma...
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ISBN:
(纸本)9781424404810
Extracting a human silhouette from an image is the enabling step for many high-level vision processing tasks, such as human tracking and activity analysis. Although there are a number of silhouette extraction and human tracking algorithms proposed in the literature, most approaches work efficiently only in constrained environments where the background is relatively simple and static. In this work, we propose to address the challenges in silhouette extraction and human tracking in a real-world unconstrained environment where the background is complex and dynamic. We extract features from image regions, accumulate the feature information over time, fuse the high-level knowledge with low-level features, and build a time-varying background model. We develop a fuzzy decision process to detach foreground moving objects from the human body. Our experimental results demonstrate that the algorithm is very efficient and robust.
Modern visual quality metrics take into account different peculiarities of the Human Visual System (HVS). One of them is described by the Weber-Fechner law and deals with the different sensitivity to distortions in im...
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ISBN:
(纸本)9780819494283
Modern visual quality metrics take into account different peculiarities of the Human Visual System (HVS). One of them is described by the Weber-Fechner law and deals with the different sensitivity to distortions in image fragments with different local mean values (intensity, brightness). We analyze how this property can be incorporated into a metric PSNR-HVS-M. It is shown that some improvement of its performance can be provided. Then, visual quality of color images corrupted by three types of i.i.d. noise (pure additive, pure multiplicative, and signal dependent, Poisson) is analyzed. Experiments with a group of observers are carried out for distorted color images created on the basis of TID2008 database. Several modern HVS-metrics are considered. It is shown that even the best metrics are unable to assess visual quality of distorted images adequately enough. The reasons for this deal with the observer's attention to certain objects in the test images, i.e., with semantic aspects of vision, which are worth taking into account in design of HVS-metrics.
In this work, we investigate how illuminant estimation techniques can be improved, taking into account automatically extracted information about the content of the images. We considered indoor/outdoor classification b...
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In this work, we investigate how illuminant estimation techniques can be improved, taking into account automatically extracted information about the content of the images. We considered indoor/outdoor classification because the images of these classes present different content and are usually taken under different illumination conditions. We have designed different strategies for the selection and the tuning of the most appropriate algorithm (or combination of algorithms) for each class. We also considered the adoption of an uncertainty class which corresponds to the images where the indoor/outdoor classifier is not confident enough. The illuminant estimation algorithms considered here are derived from the framework recently proposed by Van de Weijer and Gevers. We present a procedure to automatically tune the algorithms' parameters. We have tested the proposed strategies on a suitable subset of the widely used Funt and Ciurea dataset. Experimental results clearly demonstrate that classification based strategies outperform general purpose algorithms.
Edge detection of images is a classical problem in computer vision and imageprocessing. The key of edge detection is the choice of threshold;the choice of threshold directly determines the results of edge detection. ...
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With the advancement of Microwave Photonic (MWP) synthetic aperture radar (SAR) technology, resolution has increased to 0.02 m, and platforms have expanded from airborne to vehicle-borne. Incorporating ultra-wideband,...
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An algorithm of sequence arrangement of wavelet transform (SAWT) for infrared focal-plane arrays (IRFPA) nonuniformity correction (NUC) aiming to remote sensing image was proposed. Firstly, distribution characteristic...
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ISBN:
(纸本)9780819488411
An algorithm of sequence arrangement of wavelet transform (SAWT) for infrared focal-plane arrays (IRFPA) nonuniformity correction (NUC) aiming to remote sensing image was proposed. Firstly, distribution characteristics of pixel sequence of remote sensing image sequence were analyzed in wavelet space and scale space. Secondly, a reconstruction algorithm using mean value of approximation sequence arrangement of wavelet transform for NUC was proposed. Finally, nonuniformity of real infrared image sequence was correct by SAWT, and correction effect by SAWT compared with the algorithms of Kalman filter and Wiener filter. Results show that visual effect of SAWT is better than the other two algorithms with image sequence data quantity reduction, and the residual nonuniformity of sum image of sequence is 7-9 orders of magnitude lower than the other two algorithms, and the roughness of uniform area of image is less 0.0158-0.0544 than other algorithms. SAWT is also effective for NUC in IRFPA in less data quantity.
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