Article
Full entry |
PDF
(1.0 MB)
Feedback
PDF
(1.0 MB)
Feedback
Keywords:
multidimensional prediction; regression; scratch reconstruction
multidimensional prediction; regression; scratch reconstruction
Summary:
We present a new type of scratch removal algorithm based on a causal adaptive multidimensional prediction. The predictor use available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data but not any information from failed pixel itself. Predictor parameters cannot be directly identified so a special approximation is introduced.
References:
[1] al R. Bernstein et: Analysis and processing of Landsat-4 sensor data using advanced image processing techniques and technologies. IEEE Trans. Geosci. 22 (1984), GE-22, 192–221
[2] Broemeling L. D.: Bayesian Analysis of Linear Models. Dekker, New York 1985 MR 0772380 | Zbl 0564.62020
[3] Haindl M., Šimberová S.: A multispectral image line reconstruction method. In: Theory & Applications of Image Analysis (P. Johansen and S. Olsen, eds.), World Scientific, Singapore 1992
[4] Haindl M., Šimberová S.: A high–resolution radiospectrograph image reconstruction method. Astronom. and Astrophys., Suppl. Ser. 115 (1996), 189–193
[5] Venetianer P. L., Werblin F., Roska T., Chua L. O.: Analogic CNN algorithm for some image compression and restoration tasks. IEEE Trans. Circuit Systems CS-42 (1995), 278–284 DOI 10.1109/81.386161
Search
Partner of
