Sort Optimization Algorithm of Median Filtering Based on FPGA

Lu, Yan; Dai, Ming; Jiang, Lei; Li, Shi

doi:10.1109/mvhi.2010.145

Cited by 18 publications

(3 citation statements)

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“…These have been implemented for image processing [527,1582,1583], pattern recognition [476,1584], real-time processing [671,1477,1585], melanoma cancer detection [510,511,1586,1587], speech recognition [1587,1588] and so forth. Digital signal processing techniques implementations in FPGAs covers FFT [537,[1589][1590][1591][1592][1593], DWT [597,[1594][1595][1596][1597], time-to-digital converters [1598][1599][1600][1601][1602], DCT [580,[1603][1604][1605] and digital filters like FIR filter [56,612,[1606][1607][1608], Kalman filter [620,[1609][1610][1611], median filter [1612,1613], LMS [1614]…”

Section: Discussionmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.

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Section: Discussionmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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“…Yan Lu et al [3] proposed an optimization of sorting algorithm for median filter and its FPGA implementation. In this paper, real time median filtering using pipelining technology was presented.…”

Section: Introductionmentioning

confidence: 99%

An Efficient VLSI Architecture for Adaptive Rank Order Filter for Image Noise Removal

Hanumantharaju¹

2011

IJIEE

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“…https://oraclebo.github.io/ thors of(Garnett, Osborne, and Hennig 2013)(Lu et al 2018) use a Gaussian Process to simultaneously learn the model and the embedding. Non-linear embeddings are learnt using Variation Autoencoders in(Gómez-Bombarelli et al 2018)(Moriconi, Deisenroth, and Sesh Kumar 2020)(Lu et al 2018). ORACLEBO is agnostic to these algorithms and we expect their advantages to reflect in our performance as well.…”

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confidence: 99%

Sample-Constrained Black Box Optimization for Audio Personalization

Rajagopalan,

Wei,

Roy Choudhury

2024

AAAI

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We consider the problem of personalizing audio to maximize user experience. Briefly, we aim to find a filter h*, which applied to any music or speech, will maximize the user’s satisfaction. This is a black-box optimization problem since the user’s satisfaction function is unknown. Substantive work has been done on this topic where the key idea is to play audio samples to the user, each shaped by a different filter hi, and query the user for their satisfaction scores f(hi). A family of “surrogate” functions is then designed to fit these scores and the optimization method gradually refines these functions to arrive at the filter ˆh* that maximizes satisfaction. In certain applications, we observe that a second type of querying is possible where users can tell us the individual elements h*[j] of the optimal filter h*. Consider an analogy from cooking where the goal is to cook a recipe that maximizes user satisfaction. A user can be asked to score various cooked recipes (e.g., tofu fried rice) or to score individual ingredients (say, salt, sugar, rice, chicken, etc.). Given a budget of B queries, where a query can be of either type, our goal is to find the recipe that will maximize this user’s satisfaction. Our proposal builds on Sparse Gaussian Process Regression (GPR) and shows how a hybrid approach can outperform any one type of querying. Our results are validated through simulations and real world experiments, where volunteers gave feedback on music/speech audio and were able to achieve high satisfaction levels. We believe this idea of hybrid querying opens new problems in black-box optimization and solutions can benefit other applications beyond audio personalization.

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Sort Optimization Algorithm of Median Filtering Based on FPGA

Cited by 18 publications

References 0 publications

Field Programmable Gate Array Applications—A Scientometric Review

Field Programmable Gate Array Applications—A Scientometric Review

An Efficient VLSI Architecture for Adaptive Rank Order Filter for Image Noise Removal

Sample-Constrained Black Box Optimization for Audio Personalization

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