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检索条件"任意字段=2017 Conference on Design and Architectures for Signal and Image Processing, DASIP 2017"

共 889 条记录，以下是421-430 订阅

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USING MULTISCALE ANALYSIS FOR BLIND QUALITY ASSESSMENT OF DIBR-SYNTHESIZED imageS 24

USING MULTISCALE ANALYSIS FOR BLIND QUALITY ASSESSMENT OF DI...

引用

24th IEEE International conference on image processing (ICIP)

作者： Gu, Ke Qiao, Jun-Fei Le Callet, Patrick Xia, Zhifang Lin, Weisi Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Univ Nantes Luman Univ IRCCyN UMR 6597Polytech NantesCNRS Nantes France State Informat Ctr PR China Beijing Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9781509021758

In this paper we propose to blindly evaluate the quality of images synthesized based on a depth image-based rendering (DIBR) procedure. As an important branch in virtual reality (VR), superior DIBR techniques provide free viewpoints in many real applications such as remote surveillance and education, but few efforts have been made to measure the performance of DIBR methods (i.e. the quality of DIBR-synthesized images), especially in the condition of reference unavailable. To this aim, we put forward a new no-reference (NR) image quality assessment (IQA) model via multiscale analysis, dubbed as MSA. The design philosophy of our proposed MSA model is that the DIBR-introduced geometry distortions damage the self-similarity characteristic of natural images and the damage degrees present regular variations at distinct scales. Through systematically incorporating the measurements of the variations provided above, our MSA model can faithfully predict the quality of images generated using different DIBR technologies. Results of experiments demonstrate that the proposed blind MSA model has delivered noticeably better performance than state-of-the-art full- and no-reference IQA methods.

关键词： image quality assessment (IQA) blind/no-reference (NR) depth image-based rendering (DIBR) virtual reality (VR) multiscale analysis

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Power and Area Efficient Sorting Networks using Unary processing 35

Power and Area Efficient Sorting Networks using Unary Proces...

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35th IEEE International conference on Computer design (ICCD)

作者： Najafi, M. Hassan Lilja, David J. Riedel, Marc Bazargan, Kia Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

ISBN: (纸本)9781538622544

Sorting is a common task in a wide range of applications from signal and image processing to switching systems. For applications that require high performance, sorting is often performed in hardware. Hardware cost and power consumption are the dominant concerns. The usual approach is to wire up a network of compare-and-swap units in a configuration called a Batcher (or Bitonic) network. This paper proposes a novel area- and power-efficient approach to sorting networks based on "unary processing." Data is encoded as serial bit-streams, with values represented by the fraction of 1's in a stream of 0's and 1's. (This is an evolution of prior work on stochastic logic. Unlike stochastic logic, the unary approach is deterministic and completely accurate.) Synthesis results of complete sorting networks show up to 87% area and power saving compared to the conventional binary implementations. However, the latency increases. To mitigate the increased latency, the paper uses a novel time-encoding of data. The approach is validated with implementation of an important application of sorting: median filtering. The result is a low-cost, energy-efficient implementation of median filtering with only a slight accuracy loss.

关键词： Sorting networks unary processing time-encoding data stochastic computing median filtering low-cost design

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Color image Sharpening Using DST-Based Matrix Low-Pass Butterworth Filters 4

Color Image Sharpening Using DST-Based Matrix Low-Pass Butte...

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IEEE International conference on Consumer Electronics - Taiwan (ICCE-TW)

作者： Tseng, Chien-Cheng Lee, Su-Ling Natl Kaohsiung First Univ Sci & Technol Kaohsiung Taiwan Chang Jung Christian Univ Tainan Taiwan

ISBN: (纸本)9781509040179

In this paper, a color digital image sharpening method is developed by using discrete sine transform (DST) and matrix low-pass Butterworth filters. First, the DST method is used to design matrix Butterworth filters. Then, the un-sharp masking method and the designed matrix low-pass Butterworth filter are employed to develop a color image sharpening algorithm. Finally, Lena digital color image is used to demonstrate the usefulness of the proposed sharpening approach.

关键词： Low pass filters Band-pass filters Color Digital images Filtering algorithms image color analysis Transforms

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PaletteNet: image Recolorization with Given Color Palette 30

PaletteNet: Image Recolorization with Given Color Palette

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Cho, Junho Yun, Sangdoo Lee, Kyoungmu Choi, Jin Young Seoul Natl Univ Dept Elect & Comp Eng ASRI Seoul South Korea

ISBN: (纸本)9781538607336

image recolorization enhances the visual perception of an image for design and artistic purposes. In this work, we present a deep neural network, referred to as PaletteNet, which recolors an image according to a given target color palette that is useful to express the color concept of an image. PaletteNet takes two inputs: a source image to be recolored and a target palette. PaletteNet is then designed to change the color concept of a source image so that the palette of the output image is close to the target palette. To train PaletteNet, the proposed multi-task loss is composed of Euclidean loss and adversarial loss. The experimental results show that the proposed method outperforms the existing recolorization methods. Human experts with a commercial software take on average 18 minutes to recolor an image, while PaletteNet automatically recolors plausible results in less than a second.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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In-pixel ADC in 3D technology 15

In-pixel ADC in 3D technology

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15th IEEE International New Circuits and Systems conference (NEWCAS)

作者： Brochard, Nicolas Ginhac, Dominique Univ Bourgogne Franche Comte Le2i CNRS Arts & Metiers F-21000 Dijon France

ISBN: (纸本)9781509049912

Decreasing size of CMOS technology plays a key role in embedding more and more functionalities in CMOS image sensors. By integrating sensing with processing, new types of CMOS imaging systems can be designed and applied in domains such as machine vision, surveillance, or medical imaging. Digital pixel sensors (DPSs) are a good example of smart vision chips including image capturing and processing modules. Indeed, they incorporate, for each pixel, parallel analog-to-digital conversion thus allowing performing such conversion in early stages. Moreover, DPSs offer several benefits such as an improved SNR (signal Noise Ratio) and a wider dynamic range. In addition, the emergence of new technologies, typically CMOS 3D-IC technology, offers the opportunity to reduce pixel area and improve fill factor, making DPSs suitable for numerous fields of applications. This paper presents a digital pixel sensor (DPS) integrating an in-pixel sigma-delta analog-to-digital converter (ADC). The digital pixel includes a photodiode, a delta-sigma modulation and a digital decimation filter, featuring high-speed conversion, programmable resolutions (up to 10-bit). Based on the CMOS 130 nm 3D-IC Tezzaron technology, an optimized design of the pixel is provided, revealing a high fill-factor of about 90%.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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PhD Forum: Deep Learning Pulsed-based Convolutional Neuroprocessor Architecture on FPGAs 11

PhD Forum: Deep Learning Pulsed-based Convolutional Neuropro...

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11th International conference on Distributed Smart Cameras (ICDSC)

作者： Carballo-Hernandez, Walther Arias-Estrada, Miguel Inst Nacl Astrofis Opt & Electr Comp Sci Dept Luis Enrique Erro 1 Puebla 72840 Mexico

ISBN: (纸本)9781450354875

The biological human brain works with spiking neural networks which computational complexity is simple, compensated by the high density connection between neurons. However, most of our research in artificial neural networks is based on simplified models that need many real values processing elements of complex computing which require too much silicon space, energy and slow learning convergence. Therefore, in this brief article, it is presented a proposal for a fully digital architecture on FPGAs optimized for a highly dense intersynaptic connection on an event-based quantized Sigma-Delta pulse coding for deep Convolutional Neural Networks. This article presents early results of an approach of neuromorphic hardware design for information or pixel luminosity changes coded in time, using Sigma-Delta modulation, the design of a Pulsed Arithmetic-Logic Unit for bitstream operations with quantized weights reducing memory, from 32 bits in floating point representation, down to 1 bit. This 32x memory reduction and binary operation cells in a systolic architectures makes the integration of deep learning models feasible for embedded design like smart cameras using FPGAs.

关键词： Pulsed Arithmetic Logic Unit Pulsed Adder Pulsed Multiplier Activation function Feature map Synaptic weight Digital signal processing

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Imaging Systems and Applications, ISA 2017

Imaging Systems and Applications, ISA 2017

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Imaging Systems and Applications, ISA 2017

ISBN: (纸本)9781943580293

This proceedings contains 41 papers. This confernece aims at the latest advances in the research, engineering and systems design of imaging devices for applications in military, industrial, medical and consumer imaging. IS also focus on the design and integration of optics, sensors, digital processing and displays in imaging systems. IS captures the state-of-the-art in unique light gathering optics, image sensor architectures and technology, on and off chip digital image processing, and methods for compression and transmission. The meeting highlights the leading-edge use of imaging systems in microscopy, invasive and non-invasive surgery, remote sensing, astronomical observations and imaging from nearby planets to outer space, digital cinematography capture and projection, computational photography and consumer imaging. The key terms of this proceedings include diffraction gratings, sensors and optical design, spatial coherence illumination, spectral imaging, Talbot amplification, human photonics, hyperspectral data, multifunctional wave diagnostics, ring resonators, quantum imaging.

关键词： Imaging systems

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Robust medical image authentication using 2-D stationary wavelet transform and edge detection 2

Robust medical image authentication using 2-D stationary wav...

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2nd IET International conference on Biomedical image and signal processing, ICBISP 2017

作者： Singh, Ramanand Rawat, Paresh Shukla, Piyush AISECTUniv. Bhopal India Truba Gropu of Institute Bhoapl India UIT RGPV Bhopal India

ISBN: (纸本)9781785613180

Watermarking is a data authentication technique which embeds the watermark data within the original image in order to claim for copyright protection. Watermark techniques must be design to be robust against the various attacks. In this paper an invisible robust watermarking method is designed using edge detection in stationary wavelet transform domain. Proposed method initially decomposes the input image in to wavelet sub-band coefficients using L level SWT. The edge coefficients are calculated using the standard Sobel edge detection mask. The watermark is embedded around the edges of the high frequency sub-band SWT coefficients which lead to better invisibility. The advantage of using the SWT is its robustness against shift variations. In addition scaled morphological dilation of the low frequency sub-band is used as key along with the SWT coefficients. This in turns improves the robustness and invisibility of the watermark embedding. Performance of proposed method is tested on the four distinct categories of medical image data sets including CT scan, MRI, X ray and Fingerprints. The parametric performance is evaluated by calculating the MSE and PSNR. It is observed that proposed method not only improves the invisibility of the watermark but is robust to various attacks like cropping, compression, and interpolation. Therefore method is useful to authenticate the patients imaging data using robust watermarking.

关键词： Computerized tomography

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Content-aware Line-based Power Modeling Methodology for image signal Processor 30

Content-aware Line-based Power Modeling Methodology for Imag...

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30th IEEE International System-on-Chip conference (SOCC)

作者： Chen, Chun-Wei Shieh, Ming-Der Lu, Juin-Ming Huang, Hsun-Lun Chen, Yao-Hua Natl Cheng Kung Univ Dept Elect Engn Tainan Taiwan Ind Technol Res Inst Informat & Commun Res Labs Hsinchu Taiwan

ISBN: (纸本)9781538640340

Early power modeling and analysis using electronic system-level methodology enables designers to explore energy saving opportunities more efficiently at a higher abstraction level. However, power modeling for third party IPs are challenging due to the limited observability and unknown architecture details. To model the data dependency for black box IPs, several works rely on adopting Hamming distance of input data to approximate the switching activity, which might be not enough for modeling complex IPs such as image signal processors (ISP). This work introduces a content-aware line-based power modeling method for ISP by training an associated energy table. To effectively estimate ISP energy consumption which involves many two-dimensional data processing, this work presents a direct energy-mapping strategy using pixel luminance and gradient. Moreover, an iterative box-constrained least-squares estimation and its associated constraint refinement scheme is proposed to increase the robustness of the trained energy table even with limited training data. Simulation results show that the proposed method can reduce at least 11.54% of average error and 55.52% of max error as compared to the existing content-blind power model.

关键词： Electronic system-level design Power modeling image signal processor

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On the impact of local image texture parameters on search and localization in digital breast imaging

On the impact of local image texture parameters on search an...

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conference on Medical Imaging - image Perception, Observer Performance, and Technology Assessment

作者： Nisbett, William H. Kavuri, Amareswararao Fredette, Nathaniel R. Das, Mini Univ Houston Dept Phys Houston TX 77004 USA Univ Houston Dept Biomed Engn Houston TX 77004 USA

ISBN: (纸本)9781510607170;9781510607187

Understanding factors that influence search and localization of signals in tomographic breast imaging can allow for the development of efficient system design and image displays. Several acquisition, reconstruction and display parameters are known to influence signal (mass or microcalcification) detection. In this abstract we examine variation in relevant image texture features with respect to digital breast tomosynthesis (DBT) acquisition parameters. We shall relate the impact of these changes in detection via correlations against results obtained from human observer localization ROC (LROC) studies. Our methods included calculation and analysis of these texture features at randomly sampled ROIs in select image sets.

关键词： Digital breast tomosynthesis signal detection Breast Breast imaging Digital imaging Medical imaging Tumor growth modeling Imaging systems Statistical analysis X-ray computed tomography image display image processing Tomography

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