Increasing computational requirements in embedded mobile devices, especially with regard to imageprocessing, necessitates the use of hardware acceleration to handle higher throughputs. ARM Cortex A series of processo...
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ISBN:
(纸本)9781509032945
Increasing computational requirements in embedded mobile devices, especially with regard to imageprocessing, necessitates the use of hardware acceleration to handle higher throughputs. ARM Cortex A series of processors, which are present in a majority of mobile devices such as smartphones, feature a single instruction multiple data (SIMD) coprocessor called NEON. The wide SIMD architecture enables the parallelization of various imageprocessing operations and algorithms, resulting in significant improvements in the system throughput. This paper discusses the use of NEON Intrinsics, a C language implementation of the NEON SIMD instruction set, which is an extension of the ARM instruction set, allowing the seamless integration of optimized imageprocessing libraries with application code written in higher level languages, while maintaining performance comparable to hand optimized assembly language libraries. Several imageprocessing operations and algorithms optimized using NEON Intrinsics are benchmarked on a test bench as well as real world hardware platforms to validate the acceleration achieved in imageprocessing tasks.
Computational mathematical morphology (CMM) is a nonlinear filter representation particularly amenable to real-time imageprocessing. In the state of the art implementation each pixel value in a windowed observation i...
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ISBN:
(纸本)0819452017
Computational mathematical morphology (CMM) is a nonlinear filter representation particularly amenable to real-time imageprocessing. In the state of the art implementation each pixel value in a windowed observation is indexed into a separate lookup table to retrieve a set of bit vectors. Each bit in the vector corresponds to a basis element in the CMM filter representation. All retrieved bit vectors are "anded" together to produce a bit vector with a unique nonzero bit. The position of that bit corresponds to a basis element containing the observation and it used to look up a filter value in a table. The number of stored bit vectors is a linear function of the image or signal bit depth. We present an architecture for CMM implementation that uses a minimal number of bit vectors and required memory is less sensitive to bit depth. In the proposed architecture, basis elements are projected to subspaces and only bit vectors unique to each subspace are stored. With the addition of an intermediate lookup table to map observations to unique bit vectors, filter memory. is greatly reduced. Simulations show that the architecture provides an advantage for random tessellations of the observation space. A 50% memory savings is shown for a practical application to digital darkness control in electronic printing.
In this article, it is developed some area of issues related to data compression algorithms in the field of imageprocessing. imageprocessing area is very commonly used today with multiple applications in different f...
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ISBN:
(纸本)9781450347891
In this article, it is developed some area of issues related to data compression algorithms in the field of imageprocessing. imageprocessing area is very commonly used today with multiple applications in different fields, but also, the image compression methods or algorithms for imaging are used every day by the computer users. This paper will highlight the result of reports over the investigations or comparisons on image compression methods and will provide conclusions and ideas for further research in this area, with intense uses. Today there are a lot of different data compression methodologies, which are used to compress different data formats like, video, audio, image files. This article represents a comparison of several compression methods based on previous research and the analysis in the context of their current needs. In conclusion, this topic combines imageprocessingsystems, the advantage of using parallel programming, the benefits and results of the image compression and also the importance of some fundamental algorithms in this area.
Three classes of adaptations to systems for video processing are presented. These three techniques are special purpose modifications to commonly used algorithms. The first technique limits excursions of peak white and...
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image preliminary processing (pre-processing) of remote sensing satellites is considered as a vital process for the received data. The received video data is converted into an easy understandable raster images and any...
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ISBN:
(纸本)9780819464934
image preliminary processing (pre-processing) of remote sensing satellites is considered as a vital process for the received data. The received video data is converted into an easy understandable raster images and any distortions that results during the satellite manufacturing process or through data acquisition and transmission are eliminated. This paper proposes the pre-processingalgorithms that should be performed to the received data from remotely sensing satellites with Visible and Infra-Red (VIR) sensors beginning from reception of data by antenna at the Ground Data Reception Station (GDRS) until delivery of level 1A product (radiometrically corrected image). Briefly, the received data should be processed in two levels;level 0 to produce the raw image, and level 1 to produce radiometrically and geometrically corrected image.
The paper presents a comparative analysis of nature inspired Artificial Bee Colony and Particle Swarm Optimization algorithms for the enhancement of images. The paper briefly reviews the swarm-based algorithms. It des...
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ISBN:
(纸本)9781665424615
The paper presents a comparative analysis of nature inspired Artificial Bee Colony and Particle Swarm Optimization algorithms for the enhancement of images. The paper briefly reviews the swarm-based algorithms. It describes the dynamics of ABC and Particle Swarm Optimization algorithm and mapping for image enhancement. The key purpose of imageprocessing is to extract essential features from images. During an imageprocessing operation, the input given is an image, and its output is an enhanced high-quality image based on some characteristics/features related to that image. The mapping of the ABC and PSO algorithms for image enhancement was implemented using the Matlab imageprocessing toolbox. For both algorithms ABC and PSO, the parameters of Contrast Enhancement alpha was set in the range of 0-255 and beta was set in the range of 1-109. Finally, the Comparative Analysis of ABC and PSO algorithms was done using the metrics of Entropy, MSE and PSNR values for the images. It is found that ABC yields a better performance as compared to PSO.
In the framework of computer-aided diagnosis, pulmonary airway investigation based on multi-detector computerized tomography (MDCT) requires the development of specific tools for data interaction and analysis. The 3D ...
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ISBN:
(纸本)0819452017
In the framework of computer-aided diagnosis, pulmonary airway investigation based on multi-detector computerized tomography (MDCT) requires the development of specific tools for data interaction and analysis. The 3D segmentation of the bronchial tree provides radiologists with appropriate examination modalities such as CT bronchography, for a global analysis, or virtual endoscopy, for a local endoluminal diagnosis. Focusing on the latter modality, this paper proposes a set of advanced navigation and investigation tools based on the automatic extraction of the central axis (CA) of the 3D segmented airways. In the case of complex branching structures, Such as the bronchial tree, the automatic CA computation is a challenging problem raising several difficulties related to geometry and topology preservation. In this respect, an original approach is presented, combining 3D distance map information and geodesic front propagation in order to accurately detect branching points and to preserve the original 3D topology of the airways, irrespective to both caliber variability with the bronchial order and to bronchial wall irregularities. The CA information is represented as a multi-valued and hierarchic tree structure, making possible automatic trajectory Computation between two given points, bronchial caliber estimation in the plane orthogonal to the bronchus axis at a given location, branch indexation, and so on. These applications are Illustrated on clinical data including both normal and pathological airway morphologies.
This research presents an efficient automatic thresholding technique based on Otsu's method that can be used in edge detection algorithms and then applied as a plug-in for real-time imageprocessing devices. The p...
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This research presents an efficient automatic thresholding technique based on Otsu's method that can be used in edge detection algorithms and then applied as a plug-in for real-time imageprocessing devices. The proposed thresholding technique uses an iterative clustering based method that targets a reduced number of operations. It is well known that the Otsu calculates the global threshold splitting the image into two classes, foreground and background, and choose the threshold that minimizes the interclass variance of the threshold black and white pixels. In this paper, a faster version of Otsu's method is proposed knowing that the only pixels that have to be moved from one class to another class are the ones with values in between the previous two thresholds. This procedure yields the same set of thresholds as the original method but the redundant computation has been removed and, in this way, only few operations are required. The proposed thresholding technique has been implemented in software using C# programing language and in reconfigurable hardware on a Spartan 3E XC3S500E FPGA board using VHDL. The results obtained, presented for different digital images, confirm that the proposed iterative thresholding algorithm and architecture on FPGA can achieve the requirements to be included in real-time imageprocessingsystems.
Computed Tomography (CT) image reconstruction algorithms such as convolution back-projection (CBP) and algebraic reconstruction technique (ART) are highly compute-intensive for today's single processor systems. In...
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Computed Tomography (CT) image reconstruction algorithms such as convolution back-projection (CBP) and algebraic reconstruction technique (ART) are highly compute-intensive for today's single processor systems. In this work, we investigate the suitability of TM-1000 media processor and Analog Device's ADSP 21160 as a compute engine for the execution of image reconstruction algorithms. Philips Trimedia TM-1000, a very large instruction word (VLIW) processor, is a high performance media processor optimized for realtime processing of audio, video, graphics, and communication data streams. TM-1000 has a high performance digital signal processor (DSP) core, supported by multiple functional units. The DSP core and the functional blocks operate in parallel, driven by a mix of RISC, multimedia, SIMD-type DSP and floating point instructions. A typical DSP such as Analog Device's ADSP 21160 is based on super harvard architecture (SHARC) and is an optimized processor for digital signal processing applications. It has two sets of computation units. Each p computation unit comprises of three functional blocks namely, arithmetic and logic unit (ALU), multiplier and shifter unit. ADSP 21160 supports single instruction multiple data (SIMD) computation model to handle dual computation units. Both sets of computation units operate concurrently. We compare the performance of TM-1000 media processor and ADSP 21160 DSP processor to execute the image reconstruction algorithms by comparing the execution time of CBP and ART algorithms on them. The image reconstruction algorithms normally break down to a repetitive multiply-accumulate operation (MAC). All DSP processors support single-cycle MAC and zero-overhead loop instructions. The media processors normally do not support single-cycle MAC instruction and zero-overhead loop functionality. However, media processors are equipped with multiple functional units that perform multiple operations in a single instruction time. A DSP processor is
In this paper, various contrast and low-light image enhancement methods are described and classified into three categories: I) histogram-based, ii) transmission map-based, and iii) retinexbased. The performance of the...
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