| Project/Area Number |
16K00260
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Nagano National College of Technology |
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Principal Investigator |
Miyazaki Takashi 長野工業高等専門学校, 電気電子工学科, 嘱託教授 (10141889)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | スイッチングメジアンフィルタ / インパルス性雑音 / 雑音除去 / 閾値 / 並列処理 / エッジ強度 / 適応的閾値 / メディアンフィルタ / アルゴリズム / GPU / スイッチングメディアンフィルタ / エッジフィルタ / 画像処理 |
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| Outline of Final Research Achievements |
The multidirectional switching median filter (multi-directional SMF) that we have developed to remove impulse noise in images is effective because it features a 2×2 pixel detector and the integrated processing of multiple resulting images by multidirectional scanning. An appropriate threshold value is required for each image to remove noise. In this paper, we propose a novel method to calculate the threshold value in the noise detection process of the pixel of interest during raster scanning and a parallel algorithm using GPU, based on multidirectional SMF. The former calculates the threshold value proportional to the average value of the edge strength around the pixel of interest with a simpler process to improve the image quality, and the latter is a parallel process for high-speed processing. The effectiveness of each was confirmed by experiments.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，MDSMF 法に基づくラスタ走査中に行う雑音検出処理に対して適応的な閾値決定法を組み込んだ方法である．注目画素周辺の雑音が除去された走査済み画素を用いて局所的なエッジ量，すなわち濃度の変動量（Total Variation）から閾値を求め，その閾値を用いて雑音の判別を行う．また，走査済み画素を有効に活用することで，閾値の精度を改善し，処理の効率化を行った．また，GPUによる並列化方法も処理時間の短縮を達成した．これまで提案されるスイッチングメジアンフィルタの改良方法はアルゴリズムが複雑化する傾向にあったが，本手法は実用性の高い雑音除去方法といえる．
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