5,336 research outputs found

    Multi-Modal Enhancement Techniques for Visibility Improvement of Digital Images

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    Image enhancement techniques for visibility improvement of 8-bit color digital images based on spatial domain, wavelet transform domain, and multiple image fusion approaches are investigated in this dissertation research. In the category of spatial domain approach, two enhancement algorithms are developed to deal with problems associated with images captured from scenes with high dynamic ranges. The first technique is based on an illuminance-reflectance (I-R) model of the scene irradiance. The dynamic range compression of the input image is achieved by a nonlinear transformation of the estimated illuminance based on a windowed inverse sigmoid transfer function. A single-scale neighborhood dependent contrast enhancement process is proposed to enhance the high frequency components of the illuminance, which compensates for the contrast degradation of the mid-tone frequency components caused by dynamic range compression. The intensity image obtained by integrating the enhanced illuminance and the extracted reflectance is then converted to a RGB color image through linear color restoration utilizing the color components of the original image. The second technique, named AINDANE, is a two step approach comprised of adaptive luminance enhancement and adaptive contrast enhancement. An image dependent nonlinear transfer function is designed for dynamic range compression and a multiscale image dependent neighborhood approach is developed for contrast enhancement. Real time processing of video streams is realized with the I-R model based technique due to its high speed processing capability while AINDANE produces higher quality enhanced images due to its multi-scale contrast enhancement property. Both the algorithms exhibit balanced luminance, contrast enhancement, higher robustness, and better color consistency when compared with conventional techniques. In the transform domain approach, wavelet transform based image denoising and contrast enhancement algorithms are developed. The denoising is treated as a maximum a posteriori (MAP) estimator problem; a Bivariate probability density function model is introduced to explore the interlevel dependency among the wavelet coefficients. In addition, an approximate solution to the MAP estimation problem is proposed to avoid the use of complex iterative computations to find a numerical solution. This relatively low complexity image denoising algorithm implemented with dual-tree complex wavelet transform (DT-CWT) produces high quality denoised images

    Survey on wavelet based image fusion techniques

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    Image fusion is the process of combining multiple images into a single image without distortion or loss of information. The techniques related to image fusion are broadly classified as spatial and transform domain methods. In which, the transform domain based wavelet fusion techniques are widely used in different domains like medical, space and military for the fusion of multimodality or multi-focus images. In this paper, an overview of different wavelet transform based methods and its applications for image fusion are discussed and analysed

    Detail and contrast enhancement in images using dithering and fusion

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    This thesis focuses on two applications of wavelet transforms to achieve image enhancement. One of the applications is image fusion and the other one is image dithering. Firstly, to improve the quality of a fused image, an image fusion technique based on transform domain has been proposed as a part of this research. The proposed fusion technique has also been extended to reduce temporal redundancy associated with the processing. Experimental results show better performance of the proposed methods over other methods. In addition, achievements have been made in terms of enhancing image contrast, capturing more image details and efficiency in processing time when compared to existing methods. Secondly, of all the present image dithering methods, error diffusion-based dithering is the most widely used and explored. Error diffusion, despite its great success, has been lacking in image enhancement aspects because of the softening effects caused by this method. To compensate for the softening effects, wavelet-based dithering was introduced. Although wavelet-based dithering worked well in removing the softening effects, as the method is based on discrete wavelet transform, it lacked in aspects like poor directionality and shift invariance, which are responsible for making the resultant images look sharp and crisp. Hence, a new method named complex wavelet-based dithering has been introduced as part of this research to compensate for the softening effects. Image processed by the proposed method emphasises more on details and exhibits better contrast characteristics in comparison to the existing methods

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Fusion of Images and Videos using Multi-scale Transforms

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    This thesis deals with methods for fusion of images as well as videos using multi-scale transforms. First, a novel image fusion algorithm based primarily on an improved multi-scale coefficient decomposition framework is proposed. The proposed framework uses a combination of non-subsampled contourlet and wavelet transforms for the initial multi-scale decompositions. The decomposed multi-scale coefficients are then fused twice using various local activity measures. Experimental results show that the proposed approach performs better or on par with the existing state-of-the art image fusion algorithms in terms of quantitative and qualitative performance. In addition, the proposed image fusion algorithm can produce high quality fused images even with a computationally inexpensive two-scale decomposition. Finally, we extend the proposed framework to formulate a novel video fusion algorithm for camouflaged target detection from infrared and visible sensor inputs. The proposed framework consists of a novel target identification method based on conventional thresholding techniques proposed by Otsu and Kapur et al. These thresholding techniques are further extended to formulate novel region-based fusion rules using local statistical measures. The proposed video fusion algorithm, when used in target highlighting mode, can further enhance the hidden target, making it much easier to localize the hidden camouflaged target. Experimental results show that the proposed video fusion algorithm performs much better than its counterparts in terms of quantitative and qualitative results as well as in terms of time complexity. The relative low complexity of the proposed video fusion algorithm makes it an ideal candidate for real-time video surveillance applications

    XcalableMP PGAS Programming Language

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    XcalableMP is a directive-based parallel programming language based on Fortran and C, supporting a Partitioned Global Address Space (PGAS) model for distributed memory parallel systems. This open access book presents XcalableMP language from its programming model and basic concept to the experience and performance of applications described in XcalableMP.  XcalableMP was taken as a parallel programming language project in the FLAGSHIP 2020 project, which was to develop the Japanese flagship supercomputer, Fugaku, for improving the productivity of parallel programing. XcalableMP is now available on Fugaku and its performance is enhanced by the Fugaku interconnect, Tofu-D. The global-view programming model of XcalableMP, inherited from High-Performance Fortran (HPF), provides an easy and useful solution to parallelize data-parallel programs with directives for distributed global array and work distribution and shadow communication. The local-view programming adopts coarray notation from Coarray Fortran (CAF) to describe explicit communication in a PGAS model. The language specification was designed and proposed by the XcalableMP Specification Working Group organized in the PC Consortium, Japan. The Omni XcalableMP compiler is a production-level reference implementation of XcalableMP compiler for C and Fortran 2008, developed by RIKEN CCS and the University of Tsukuba. The performance of the XcalableMP program was used in the Fugaku as well as the K computer. A performance study showed that XcalableMP enables a scalable performance comparable to the message passing interface (MPI) version with a clean and easy-to-understand programming style requiring little effort

    Proceedings of the 15th International Workshop on Beryllium Technology (BeWS-15) September, 14-15, 2022, Karlsruhe, Germany (KIT Scientific Reports ; 7764)

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    The 15th International Workshop on Beryllium Technology (BeWS-15) was held as a joint event combining BeWS-15 and industrial forum BeYOND-IX on September 14-15, 2022 in Karlsruhe, Germany with great success as a hybrid event. The workshop was organized by the Karlsruhe Institute of Technology. Participants came from Germany, the US, the UK, Kazakhstan, Latvia, Czech Republic, Japan, Sweden, France and China, totaling 55 persons, which was not expected immediately after the global pandemic

    The Sixth Annual Workshop on Space Operations Applications and Research (SOAR 1992)

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    This document contains papers presented at the Space Operations, Applications, and Research Symposium (SOAR) hosted by the U.S. Air Force (USAF) on 4-6 Aug. 1992 and held at the JSC Gilruth Recreation Center. The symposium was cosponsored by the Air Force Material Command and by NASA/JSC. Key technical areas covered during the symposium were robotic and telepresence, automation and intelligent systems, human factors, life sciences, and space maintenance and servicing. The SOAR differed from most other conferences in that it was concerned with Government-sponsored research and development relevant to aerospace operations. The symposium's proceedings include papers covering various disciplines presented by experts from NASA, the USAF, universities, and industry

    Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

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    The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations
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