Compression of high dynamic infrared image using auto aggregation algorithm

• Autorzy: Fidali M. , Jamrozik W.
• Języki publikacji: EN

Abstrakty

EN

The article presents a method of compression of High Dynamic Range of infrared image and its details enhancement. The method is based on aggregation of partial images with different ranges of pixel values generated using a weighting function. Aggregation of images could be performed according to proposed scheme with use of the optimal algorithm selected by user. Preliminary results shown that the method can reveal previously hidden details in the original image.

Słowa kluczowe

EN

infrared image; compression; enhancement; high dynamic

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2017
• Tom: Vol. 63, No. 4
• Strony: 146--149
• Opis fizyczny: Bibliogr. 8 poz., rys., tab., wzory

Twórcy

autor

Fidali M.

• Silesian University of Technology, Faculty of Mechanical Engineering 18a Konarskiego St., 44-100 Gliwice, Poland

autor

Jamrozik W.

• Silesian University of Technology, Faculty of Mechanical Engineering 18a Konarskiego St., 44-100 Gliwice, Poland

Bibliografia

• [1] Ning L., Zhao D.: Detail enhancement for high-dynamic-range infrared images based on guided image filter. Infrared Physics & Technology 67 (2014), pp. 138–147.
• [2] Silverman J.: Display and enhancement of infrared images. In International Conference on Image Processing and its Applications, pp. 345–348 (1992).
• [3] Zuiderveld K.: Contrast limited adaptive histogram equalization. In Graphics Gems IV, pp. 474–485, Academic Press Professional, Inc., San Diego (1994).
• [4] Zuo C., Chen Q., Liu N., Ren J., Sui X.: Display and detail enhancement for high-dynamic-range infrared images. Opt. Eng. 50, 127401 (2011).
• [5] Fidali M, Jamrozik W.: The method of Compression of High-Dynamic-Range Infrared Images using image aggregation algorithms. 13th Quantitative InfraRed Thermography Conference, July 4-8, 2016, Gdańsk Poland.
• [6] Piella G.: A general framework for multiresolution image fusion: from pixels to regions. Information Fusion, 4:259–280, 2003.
• [7] Pajares Gonzalo, de la Cruz Jesús Manuel: A wavelet-based image fusion tutorial, Pattern Recognition, Volume 37, Issue 9, September 2004, Pages 1855-1872, ISSN 0031-3203 http://dx.doi.org/10.1016/ j.patcog.2004.03.010.
• [8] Sujoy Paul, Sevcenco Ioana S., Agathoklis Panajotis: Multi-Exposure and Multi-Focus Image Fusion in Gradient Domain, Journal of Circuits, Systems, and Computers. Vol. 25, No. 10 (2016) 1650123 (18 pages), World Scientific Publishing Company. DOI: 10.1142/S0218126616501231

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).