부동소수점 형식 이미지를 위한 효율적인 중간값 필터알고리즘
An Efficient Median Filter Algorithm for Floating-point Images
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
픽셀의 정보를 실숫값으로 표현하는 부동소수점 형식 이미지는 HDR 이미지 등에서 사용된다. 효율적인 중간값 필터 알고리즘에관한 연구는 다양하게 이뤄졌지만 대부분 8비트 깊이 이하의 이미지에 적용할 수 있고 부동소수점 형식 이미지에 적용할 수 있는알고리즘은 Gil과 Werman의 알고리즘을 비롯하여 제한적으로만 존재한다. 본 논문에서는 Gil과 Werman의 알고리즘을 개선한Kim의 알고리즘을 다시 개선하여 부동소수점 형식 이미지에 대해 효율적으로 동작하는 중간값 필터 알고리즘을 제안한다. 반복적으로 사용되는 이진 탐색 트리에 대한 중복 작업을 줄이고 역인덱스를 적용하여 실험 결과 Kim 알고리즘보다 약 10% 수행시간이향상됨을 보인다.
Abstract
Floating-point images that express pixel information as real numbers are used in HDR images. There have beenvarious researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth imagesand there are only a few number of algorithms applicable to floating-point images, including Gil and Werman’salgorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images byimproving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that theexecution time is improved by about 10% compared to the Kim’s algorithm by reducing the redundant work forthe repetitively used binary search tree and applying the inverted index.
참고문헌 (18)
- M. Le Pendu, "Adaptive Re-Quantization for High Dynamic Range Video Compression", Proc. of 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.7367~7371 (2014)
- A. Darmont, "High Dynamic Range Imaging:Sensors and Architectures" (2013), SPIE press
- Tao Fang, "On performance of lossless compression for HDR image quantized in color space", Signal Processing: Image Communication, 24(5), pp.397~404 (2009), Elsevier BV[DOI]
- R. Chityala, "Image Processing and Acquisition using Python" (2021), CRC Press
- P. Maragos, "Morphological filters--Part II: Their relations to median, order-statistic, and stack filters", IEEE Transactions on Acoustics, Speech, and Signal Processing, 35(8), pp.1170~1184 (1987), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- D. Mayerich, "NOISE AND ARTIFACT REMOVAL IN KNIFE-EDGE SCANNING MICROSCOPY", 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.556~559 (2007), IEEE
- Y. Choe, "HighThroughput Image Reconstruction and Analysis:Intelligent Microscopy Applications", pp.11~37 (2008)
- J. Lee, "Mapping the Full Vascular Network in the Mouse Brain at Submicrometer Resolution", 39th Annual International Conference of the IEEE EMBC (2017)
- T. Huang, "A fast two-dimensional median filtering algorithm", IEEE Transactions on Acoustics, Speech, and Signal Processing, 27(1), pp.13~18 (1979), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Ben Weiss, "Fast median and bilateral filtering", ACM Transactions on Graphics, 25(3), pp.519~526 (2006), Association for Computing Machinery (ACM)[DOI]
- Simon Perreault, "Median Filtering in Constant Time", IEEE Transactions on Image Processing, 16(9), pp.2389~2394 (2007), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- A. Alekseychuk, "Hierarchical Recursive Running Median", IEEE International Conference on Image Processing, pp.109~112 (2012)
- Krystine Dawn Sherwin, "Median Filters on FPGAs for Infinite Data and Large, Rectangular Windows", ACM Transactions on Reconfigurable Technology and Systems, 15(4), pp.1~24 (2022), Association for Computing Machinery (ACM)[DOI]
- P. Szántó, "Hierarchical Histogram-based Median Filter for GPUs", Acta Polytechnica Hungarica, 15(2), pp.49~68 (2018)
- "Communications of the ACM", 1975, 173~
- "2009", ~
- J. Gil, "Computing 2-D min, median, and max filters", IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(5), pp.504~507 (1993), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- 김진욱, "16비트 깊이 이상의 이미지에서의 중간값 필터 계산", 전기전자학회논문지, 24(2), pp.507~513 (2020), 한국전기전자학회[DOI]