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https://doi.org/10.2498/cit.1000677

Missing Data Correction in Still Images Using Multi-Resolution Analysis

Danco Davcev
Vladimir Trajkovik
Blerim Mustafa

Puni tekst: engleski, pdf (510 KB) str. 1-5 preuzimanja: 805* citiraj
APA 6th Edition
Davcev, D., Trajkovik, V. i Mustafa, B. (2007). Missing Data Correction in Still Images Using Multi-Resolution Analysis. Journal of computing and information technology, 15 (1), 1-5. https://doi.org/10.2498/cit.1000677
MLA 8th Edition
Davcev, Danco, et al. "Missing Data Correction in Still Images Using Multi-Resolution Analysis." Journal of computing and information technology, vol. 15, br. 1, 2007, str. 1-5. https://doi.org/10.2498/cit.1000677. Citirano 02.03.2021.
Chicago 17th Edition
Davcev, Danco, Vladimir Trajkovik i Blerim Mustafa. "Missing Data Correction in Still Images Using Multi-Resolution Analysis." Journal of computing and information technology 15, br. 1 (2007): 1-5. https://doi.org/10.2498/cit.1000677
Harvard
Davcev, D., Trajkovik, V., i Mustafa, B. (2007). 'Missing Data Correction in Still Images Using Multi-Resolution Analysis', Journal of computing and information technology, 15(1), str. 1-5. https://doi.org/10.2498/cit.1000677
Vancouver
Davcev D, Trajkovik V, Mustafa B. Missing Data Correction in Still Images Using Multi-Resolution Analysis. Journal of computing and information technology [Internet]. 2007 [pristupljeno 02.03.2021.];15(1):1-5. https://doi.org/10.2498/cit.1000677
IEEE
D. Davcev, V. Trajkovik i B. Mustafa, "Missing Data Correction in Still Images Using Multi-Resolution Analysis", Journal of computing and information technology, vol.15, br. 1, str. 1-5, 2007. [Online]. https://doi.org/10.2498/cit.1000677

Sažetak
This paper proposes an improvement to the texture generation – based image in-painting algorithm, using multi-resolution analysis. Instead of optimizing the size of the neighborhood window of the synthesized pixel and the size of the test image, the approach described in this paper applies the same (minimal) window and test image size to different sub-bands of the discrete wavelet transformed (DWT) image. This way the execution complexity is kept lowest possible, while still obtaining the same visual quality as by applying the optimal parameters in the spatial domain.

Hrčak ID: 44632

URI
https://hrcak.srce.hr/44632

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