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.
In this paper a method for estimating mean opinion score for noisy images is presented. The focus is to create a robust method, which is not suited to the single image database. Algorithm is validated using three diff...
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ISBN:
(纸本)9781538669792
In this paper a method for estimating mean opinion score for noisy images is presented. The focus is to create a robust method, which is not suited to the single image database. Algorithm is validated using three different databases, which shows that it is more generic than other methods. Moreover, proposed solution works as non-reference image quality assessment algorithm, which means that only distorted image is used for evaluation. Results obtained with proposed method are compared with two other algorithms designed for non-reference IQA.
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.
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.
Assessment of the resolution properties of nonlinear imaging systems is a useful but challenging task. While the modulation transfer function (MTF) fully describes contrast resolution as a function of spatial frequenc...
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ISBN:
(纸本)9780819494429
Assessment of the resolution properties of nonlinear imaging systems is a useful but challenging task. While the modulation transfer function (MTF) fully describes contrast resolution as a function of spatial frequency for linear systems, an equivalent metric does not exist for systems with significant nonlinearity. Therefore, this preliminary investigation attempts to classify and quantify the amount of scaling and distortion imposed on a given image signal as the result of a nonlinear process (nonlinear imageprocessing algorithm). As a proof-of-concept, a median filter is assessed in terms of its principle frequency response (PFR) and distortion response (DR) functions. These metrics are derived in frequency space using a sinusoidal basis function, and it is shown that, for a narrow-band sinusoidal input signal, the scaling and distortion properties of the nonlinear filter are described exactly by PFR and DR, respectively. The use of matched sinusoidal basis and input functions accurately reveals the frequency response to long linear structures of different scale. However, when more complex (multi-band) input signals are considered, PFR and DR fail to adequately characterize the frequency response due to nonlinear interaction effects between different frequency components during processing. Overall, the results reveal the context-dependent nature of nonlinear imageprocessing algorithm performance, and they emphasize the importance of the basis function choice in algorithm assessment. In the future, more complex forms of nonlinear systems analysis may be necessary to fully characterize the frequency response properties of nonlinear algorithms in a context-dependent manner
In this paper we examine the problem of bit allocation in lossy image set compression. Instead of treating each image independently, image set compression algorithms examine the relationships among similar images and ...
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ISBN:
(纸本)9789531841917
In this paper we examine the problem of bit allocation in lossy image set compression. Instead of treating each image independently, image set compression algorithms examine the relationships among similar images and remove inter-image redundancies to improve compression performance. These algorithms map the original image set into a number of prediction residual images to be coded. Typically the same bit rate is used to encode each residual. We show that a rate-distortion approach based on Lagrangian optimization can lead to further improvement in image set compression algorithms.
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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Product requirements often dictate the use of off-the-shelf processors for very fast signal processing applications. Additionally, restrictions on cost, power, or size/weight may preclude the use of specialized vector...
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ISBN:
(纸本)0780370414
Product requirements often dictate the use of off-the-shelf processors for very fast signal processing applications. Additionally, restrictions on cost, power, or size/weight may preclude the use of specialized vector processors for implementation of the algorithms. We discuss a new method for performing signed parallel processing in scalar, off-the-shelf processors for integerized signal processingalgorithms. Uniform data precision may be used, but is not required for the method. It is shown that the reduction in execution cycles resulting from this implementation is approximately linear in the size of the registers, divided by the precision required.
image fusion is the process of combining multiple images into a single image which retains the most pertinent information from each original image source. More recently, multi-scale image fusion approaches have emerge...
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ISBN:
(纸本)9781424465880
image fusion is the process of combining multiple images into a single image which retains the most pertinent information from each original image source. More recently, multi-scale image fusion approaches have emerged as a means of providing a more meaningful fusion which better reflects the human visual system. In this paper, multi-scale decomposition techniques and image fusion algorithms are adapted using the Parameterized Logarithmic imageprocessing (PLIP) model, a nonlinear imageprocessing framework which more accurately processes images. Experimental results via computer simulations illustrate the improved performance of the proposed algorithms by both qualitative and quantitative means.
In the paper we present a method for increasing the quality of views synthesized with typical Depth-image-Based Rendering (DIBR) view synthesis algorithms. In the proposed idea the resolution of input real views and c...
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ISBN:
(纸本)9781509063444
In the paper we present a method for increasing the quality of views synthesized with typical Depth-image-Based Rendering (DIBR) view synthesis algorithms. In the proposed idea the resolution of input real views and corresponding depth maps is doubled before the view synthesis. After the synthesis, the resolution of a synthesized view is downsampled back to the original resolution. This approach is transparent for the view synthesis algorithms, thus can be used with any DIBR method. In the paper, tests for two synthesis algorithms (the state-of-the-art MPEG reference software and our view synthesis method) are presented. For both algorithms, the proposed upsampling improves objective and subjective quality of synthesized views.
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