"JOURNAL OF RADIO ELECTRONICS" (Zhurnal Radioelektroniki ISSN 1684-1719, N 10, 2018

contents of issue      DOI  10.30898/1684-1719.2018.10.6     full text in Russian (pdf)  

UDC 004.932.4

Digital imaging system with hardware implementation on Xilinx PLD


D. A. Gavrilov 1, A. V. Pavlov 2, D. N. Shchelkunov 1

1 Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow Region, 141701, Russian Federation

2 Lebedev Institute of Precision Mechanics and Computer Engineering (IPMCE) 119991, Moscow, Leninsky prospect, 51


The paper is received on September 28, 2018


Abstract. Introduction: technologies of computer vision are widely used in many fields of science and industry. The tasks of vision systems are the acquisition, transmission, reproduction and processing of visual information without loss of information. Algorithms and filters used for preprocessing are designed to suppress noise, retrieve, and store information necessary for further processing. Purpose: the development of a digital image processing module with hardware implementation on the Xillerx XC7Z020-2CLG400I crystal XC7Z020-2CLG400I chip Xilinx, which allows the HDR image to be compressed without loss of image detail and high processing speed. Results: In the presented work, the image processing system based on computer vision technology was developed. The analysis of filters for image processing is carried out, drawbacks and advantages of the bilateral and guided filters are considered, on the basis of which the filter is selected. The algorithm of the selected controlled filter is presented. The hardware implementation of the selected filter on the programmable logic is performed. The authors conducted an effective method for optimizing the guided filter using the integrated image representation and reducing its bit depth, which allowed to increase the efficiency of the filter and to compress the HDR image without loss of quality and with high processing speed. Practical relevance: The developed algorithm provides noise suppression and storage of information necessary for further processing.

Keywords: image processing, bilaterial filter, guided filter, HDR image, HDR image compression, integrated image representation, resource optimization.


1.     Gonzalez R.C., Woods R.E. Digital image processing. 2nd ed. published by Pearson Education, Inc, publishing as Prentice Hall. 2002. ISBN: 978-0-2011-8075-6.

2.     He K., Sun J., Tang X. Guided Image Filtering. Proc. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2013. Vol.35. No.6. pp. 1397-1409.

3.     Tomasi C., Manduchi R. Bilateral filtering for gray and color images. Proc. IEEE International Conference on Computer Vision. 1998. pp. 839-846.

4.     Petschnigg G., Agrawala M., Hoppe H., Szeliski R., Cohen M., Toyama K. Digital Photography with Flash and No-Flash Image Pairs.  ACM Transactions on Graphics. 2004. Vol.23. No.3. pp. 664-672.

5.     Wong W.C.K., Chung A.C.S., Yu S.C.H. Trilateral filtering for biomedical images. Proc. IEEE International Symposium on Biomedical Imaging. 2004. pp. 820-823.

6.     Liu C., Freeman W.T., Szeliski R., Kang S.B. Noise estimation from a single image. Proc. IEEE Conference on Computer Vision and Pattern Recognition. 2006. pp. 901-908.

7.     Durand F., Dorsey J. Fast bilateral filtering for the display of high-dynamic-range images. ACM Transactions on Graphics. 2002. Vol.4. No.3. pp. 257-266.

8.     Bae T.-W., Sohng K.-I. Small target detection using bilateral filter based on edge component.  Infrared, Millimeter and Terahertz Waves. 2010. Vol.31. pp. 735-743.

9.     Eisemann E., Durand F. Flash Photography Enhancement via Intrinsic Relighting.  ACM Transactions on Graphics. 2004. Vol.23. No.3. pp. 673-678.

10.  Porikli F. Constant time O(1) bilateral filtering.  Proc. IEEE Conference on Computer Vision and Pattern Recognition, 2008, pp. 1-8.

11.  Farbman Z., Fattal R., Lischinski D., Szeliski R. Edge-preserving decompositions for multi-scale tone and detail manipulation.  ACM Transactions on Graphics. 2008. Vol.27. No.3. pp. 67.

12.  Bae S., Paris S., Durand F. Two-scale tone management for photographic look.  ACM Transactions on Graphics. 2006. Vol.25. No.3. pp. 637-645.

13.  Krapchatova T.V., Filippov M.V. Analysis of the effectiveness of algorithms for bilateral filtration.  Electronic Journal: Science and Education. 2012. No.2. Available at http://technomag.bmstu.ru/doc/340957.html (In Russian)

14.  Weiss B. Fast median and bilateral filtering.  ACM Transactions on Graphics, 2006, Vol.25. No.3. pp. 519-526.

15.  Yang Q., Tan K.-H., Ahuja N. Real-time O(1) bilateral filtering.  Proc. IEEE Conference on Computer Vision and Pattern Recognition, 2009, pp. 557564.

16.  Fleishman S., Drori I., Cohen-Or D. Bilateral mesh denoising. ACM Transactions on Graphics. 2003. Vol.22. No.3. pp. 943-949.

17.  Jones T.R., Durand F., Desbrun M. Non-iterative, feature-preserving mesh smoothing.  ACM Transactions on Graphics. 2003. Vol.22. No.3. pp. 943-949.

18.  Oh B.M., Chen M., Dorsey J., Durand F. Image-bases modeling and photo editing. Proc. ACM SIGGRAPH. 2001. pp. 433-442.


For citation:

D. A. Gavrilov, A. V. Pavlov, D. N. Shchelkunov. Digital imaging system with hardware implementation on Xilinx PLD. Zhurnal Radioelektroniki - Journal of Radio Electronics. 2018. No. 10. Available at http://jre.cplire.ru/jre/oct18/6/text.pdf

DOI  10.30898/1684-1719.2018.10.6