{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T05:01:53Z","timestamp":1764997313171,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T00:00:00Z","timestamp":1597968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["No. 2019-0-01351"],"award-info":[{"award-number":["No. 2019-0-01351"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The range kernel of bilateral filter degrades image quality unintentionally in real environments because the pixel intensity varies randomly due to the noise that is generated in image sensors. Furthermore, the range kernel increases the complexity due to the comparisons with neighboring pixels and the multiplications with the corresponding weights. In this paper, we propose a noise-aware range kernel, which estimates noise using an intensity difference-based image noise model and dynamically adjusts weights according to the estimated noise, in order to alleviate the quality degradation of bilateral filters by noise. In addition, to significantly reduce the complexity, an approximation scheme is introduced, which converts the proposed noise-aware range kernel into a binary kernel while using the statistical hypothesis test method. Finally, blue a fully parallelized and pipelined very-large-scale integration (VLSI) architecture of a noise-aware bilateral filter (NABF) that is based on the proposed binary range kernel is presented, which was successfully implemented in field-programmable gate array (FPGA). The experimental results show that the proposed NABF is more robust to noise than the conventional bilateral filter under various noise conditions. Furthermore, the proposed VLSI design of the NABF achieves 10.5 and 95.7 times higher throughput and uses 63.6\u201397.5% less internal memory than state-of-the-art bilateral filter designs.<\/jats:p>","DOI":"10.3390\/s20174722","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T09:21:51Z","timestamp":1598001711000},"page":"4722","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Noise-Aware and Light-Weight VLSI Design of Bilateral Filter for Robust and Fast Image Denoising in Mobile Systems"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6992-408X","authenticated-orcid":false,"given":"Sung-Joon","family":"Jang","sequence":"first","affiliation":[{"name":"Intelligent Image Processing Research Center, Korea Electronics Technology Institute, Seongnam 13509, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3400-0493","authenticated-orcid":false,"given":"Youngbae","family":"Hwang","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering, Chungbuk National University, Cheongju 28644, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.inffus.2019.09.003","article-title":"Image denoising review: From classical to state-of-the-art approaches","volume":"55","author":"Goyal","year":"2020","journal-title":"Inf. Fusion"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3695","DOI":"10.1109\/TIP.2020.2964518","article-title":"Connecting Image Denoising and High-Level Vision Tasks via Deep Learning","volume":"29","author":"Liu","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1134\/S1054661817040149","article-title":"Towards reliable object detection in noisy images","volume":"27","author":"Milyaev","year":"2017","journal-title":"Pattern Recognit. Image Anal."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/s13640-018-0264-z","article-title":"Improved BM3D image denoising using SSIM-optimized Wiener filter","volume":"2018","author":"Hasan","year":"2018","journal-title":"EURASIP J. Image Video Process."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Song, Y., Zhu, Y., and Du, X. (2019). Dynamic Residual Dense Network for Image Denoising. Sensors, 19.","DOI":"10.3390\/s19173809"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Lefkimmiatis, S. (2018, January 18\u201322). Universal denoising networks: A aovel CNN architecture for image denoising. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00338"},{"key":"ref_7","unstructured":"Tomasi, C., and Manduchi, R. (1998, January 4\u20137). Bilateral filtering for gray and color images. Proceedings of the IEEE International Conference on Computer Vision, Bombay, India."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1186\/s13640-016-0137-2","article-title":"A parallel camera image signal processor for SIMD architecture","volume":"2016","author":"Choi","year":"2016","journal-title":"EURASIP J. Image Video Process."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Petreto, A., Romera, T., Lemaitre, F., Masliah, I., Gaillard, B., Bouyer, M., Meunier, Q.L., and Lacassagne, L. (2019, January 16\u201318). A new real-time embedded video denoising algorithm. Proceedings of the Conference on Design and Architectures for Signal and Image Processing, Montreal, QC, Canada.","DOI":"10.1109\/DASIP48288.2019.9049189"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3231","DOI":"10.1109\/TIP.2011.2159226","article-title":"A 124 Mpixels\/s VLSI design for histogram-based joint bilateral filtering","volume":"20","author":"Tseng","year":"2011","journal-title":"IEEE Trans. Image Process."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Dutta, H., Hannig, F., Teich, J., Heigl, B., and Hornegger, H. (2006, January 11\u201313). A design methodology for hardware acceleration of adaptive filter algorithms in image processing. Proceedings of the IEEE International Conference on Application-specific Systems, Architectures and Processors, Steamboat Springs, CO, USA.","DOI":"10.1109\/ASAP.2006.4"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4093","DOI":"10.1109\/TIE.2013.2284133","article-title":"An FPGA-based fully synchronized design of a bilateral filter for real-time image denoising","volume":"61","author":"Kube","year":"2014","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1109\/TIE.2017.2726960","article-title":"A Reconfigurable and Scalable FPGA Architecture for Bilateral Filtering","volume":"65","author":"Dabhade","year":"2018","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_14","unstructured":"Tsin, Y., Ramesh, V., and Kanade, T. (2001, January 7\u201314). Statistical calibration of CCD imaging process. Proceedings of the IEEE International Conference on Computer Vision, Vancouver, BC, Canada."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.1109\/TPAMI.2011.224","article-title":"Difference-based image noise modeling using skellam Distribution","volume":"34","author":"Hwang","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s10654-016-0149-3","article-title":"Statistical tests, P values, confidence intervals, and power: A guide to misinterpretations","volume":"31","author":"Greenland","year":"2016","journal-title":"Eur. J. Epidemiol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Peng, H., and Rao, R. (2010, January 26\u201329). Bilateral kernel parameter optimization by risk minimization. Proceedings of the IEEE International Conference on Image Processing, Hong Kong, China.","DOI":"10.1109\/ICIP.2010.5651045"},{"key":"ref_18","unstructured":"Kishan, H., and Seelamantula, C.S. (October, January 30). Optimal parameter selection for bilateral filters using Poisson Unbiased Risk Estimate. Proceedings of the IEEE International Conference on Image Processing, Orlando, FL, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1109\/LSP.2013.2293592","article-title":"Optimization of bilateral filter parameters via chi-square unbiased risk estimate","volume":"21","author":"Chen","year":"2014","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Luisier, F., and Wolfe, P.J. (2011, January 11\u201314). Chi-square unbiased risk estimate for denoising magnitude MR images. Proceedings of the IEEE International Conference on Image Processing, Brussels, Belgium.","DOI":"10.1109\/ICIP.2011.6115745"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1007\/s10278-018-0110-y","article-title":"An automatic parameter decision system of bilateral filtering with GPU-Based acceleration for brain MR images","volume":"32","author":"Chang","year":"2018","journal-title":"J. Digit. Imaging"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Porikli, F. (2008, January 23\u201328). Constant time O(1) bilateral filtering. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska.","DOI":"10.1109\/CVPR.2008.4587843"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2519","DOI":"10.1109\/TIP.2016.2548363","article-title":"Fast and provably accurate bilateral filtering","volume":"25","author":"Chaudhury","year":"2016","journal-title":"IEEE Trans. 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