TY - GEN
T1 - Acceleration of Gaussian Filter with Short Window Length Using DCT-1
AU - Yano, Takahiro
AU - Sugimoto, Kenjiro
AU - Kuroki, Yoshimitsu
AU - Kamata, Sei Ichiro
N1 - Funding Information:
This work was partly supported by JSPS KAKENHI (No. JP16K16092, JP17H01764, and JP18K18076).
Publisher Copyright:
© 2018 APSIPA organization.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - This paper presents an accelerated constant-time Gaussian filter (O(1) GF) specialized in short window length where constant-time (O(1)) means that computational complexity per pixel does not depend on filter window length. Our method is extensively designed based on the idea of O(1) GF based on Discrete Cosine Transform (DCT). This framework approximates a Gaussian kernel by a linear sum of cosine terms and then convolves each cosine term in O(1) per pixel using sliding transform. Importantly, if window length is short, DCT-1 consists of easily-computable cosine values such as 0, \pm\frac{1}{2} and ±1. This behavior is not satisfied in other DCT types. From this fact, our method accelerates the sliding transform by employing DCT-1 focusing on short window length. Experiments show that our method overcomes naive Gaussian convolution and existing O(1) GF in terms of computational time. Interestingly, the results also reveal that, without truncating negligible terms, our method runs faster than convolution.
AB - This paper presents an accelerated constant-time Gaussian filter (O(1) GF) specialized in short window length where constant-time (O(1)) means that computational complexity per pixel does not depend on filter window length. Our method is extensively designed based on the idea of O(1) GF based on Discrete Cosine Transform (DCT). This framework approximates a Gaussian kernel by a linear sum of cosine terms and then convolves each cosine term in O(1) per pixel using sliding transform. Importantly, if window length is short, DCT-1 consists of easily-computable cosine values such as 0, \pm\frac{1}{2} and ±1. This behavior is not satisfied in other DCT types. From this fact, our method accelerates the sliding transform by employing DCT-1 focusing on short window length. Experiments show that our method overcomes naive Gaussian convolution and existing O(1) GF in terms of computational time. Interestingly, the results also reveal that, without truncating negligible terms, our method runs faster than convolution.
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U2 - 10.23919/APSIPA.2018.8659511
DO - 10.23919/APSIPA.2018.8659511
M3 - Conference contribution
AN - SCOPUS:85063442690
T3 - 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
SP - 129
EP - 132
BT - 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
Y2 - 12 November 2018 through 15 November 2018
ER -