In signal processing, particularly image processing, total variation denoising, also known as total variation regularization or total variation filtering, is a noise removal process (filter). It is based on the principle that signals with excessive and possibly spurious detail have high total variation, that is, the integral of the absolute image gradient is high. According to this principle, reducing the total variation of the signal—subject to it being a close match to the original signal—removes unwanted detail whilst preserving important details such as edges. The concept was pioneered by L. I. Rudin, S. Osher, and E. Fatemi in 1992 and so is today known as the ROF model.
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| - Regolarizzazione a variazione totale (it)
- Total variation denoising (en)
- 總變差去噪 (zh)
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| - 總變差去噪（英語：Total Variation Denoising）是訊號處理中一種常見的降噪方法，於1992年由L. I. Rudin、和E. Fatemi提出，因此亦稱為ROF模型。一個含有雜訊的訊號相較於其未受雜訊影響的訊號，會有較大的總變差值，即其梯度絕對值的總和較大。因此若能找到一個與原始訊號相似且總變差較小的訊號，即可作為原始訊號的降噪結果。此算法可以在去除雜訊的同時保留邊緣，即使在低訊號雜訊比的情況下，依然能有效的去噪和保留邊緣。 (zh)
- La regolarizzazione a variazione totale (anche nota come total variation denoising) è un metodo di riduzione del rumore usato in elaborazione digitale delle immagini, basato sul principio che la presenza di rumore causa un incremento della del segnale. Per questo motivo, una riduzione della variazione totale di un segnale, condotta sotto il vincolo di mantenere similitudine con il segnale originario, può essere usata per rimuovere il rumore e allo stesso tempo conservare i contenuti significativi. Il metodo è stato introdotto da Rudin, Osher e Fatemi nel 1992, motivo per cui è anche noto come modello ROF. (it)
- In signal processing, particularly image processing, total variation denoising, also known as total variation regularization or total variation filtering, is a noise removal process (filter). It is based on the principle that signals with excessive and possibly spurious detail have high total variation, that is, the integral of the absolute image gradient is high. According to this principle, reducing the total variation of the signal—subject to it being a close match to the original signal—removes unwanted detail whilst preserving important details such as edges. The concept was pioneered by L. I. Rudin, S. Osher, and E. Fatemi in 1992 and so is today known as the ROF model. (en)
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| - In signal processing, particularly image processing, total variation denoising, also known as total variation regularization or total variation filtering, is a noise removal process (filter). It is based on the principle that signals with excessive and possibly spurious detail have high total variation, that is, the integral of the absolute image gradient is high. According to this principle, reducing the total variation of the signal—subject to it being a close match to the original signal—removes unwanted detail whilst preserving important details such as edges. The concept was pioneered by L. I. Rudin, S. Osher, and E. Fatemi in 1992 and so is today known as the ROF model. This noise removal technique has advantages over simple techniques such as linear smoothing or median filtering which reduce noise but at the same time smooth away edges to a greater or lesser degree. By contrast, total variation denoising is remarkably effective edge-preserving filter, i.e., simultaneously preserving edges whilst smoothing away noise in flat regions, even at low signal-to-noise ratios. (en)
- La regolarizzazione a variazione totale (anche nota come total variation denoising) è un metodo di riduzione del rumore usato in elaborazione digitale delle immagini, basato sul principio che la presenza di rumore causa un incremento della del segnale. Per questo motivo, una riduzione della variazione totale di un segnale, condotta sotto il vincolo di mantenere similitudine con il segnale originario, può essere usata per rimuovere il rumore e allo stesso tempo conservare i contenuti significativi. Il metodo è stato introdotto da Rudin, Osher e Fatemi nel 1992, motivo per cui è anche noto come modello ROF. Rispetto a tecniche di riduzione del rumore come l'applicazione di un filtro gaussiano o di un filtro mediano, il metodo ha il vantaggio di essere particolarmente efficace nell'eliminare il rumore e allo stesso tempo meglio preservare i contorni, anche in caso di basso rapporto segnale/rumore. (it)
- 總變差去噪（英語：Total Variation Denoising）是訊號處理中一種常見的降噪方法，於1992年由L. I. Rudin、和E. Fatemi提出，因此亦稱為ROF模型。一個含有雜訊的訊號相較於其未受雜訊影響的訊號，會有較大的總變差值，即其梯度絕對值的總和較大。因此若能找到一個與原始訊號相似且總變差較小的訊號，即可作為原始訊號的降噪結果。此算法可以在去除雜訊的同時保留邊緣，即使在低訊號雜訊比的情況下，依然能有效的去噪和保留邊緣。 (zh)
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