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g) Perform steps e and f repeatedly for all blocks in the frame.
While the above approach to local thresholds is simple and conceptual, it however considers each block independent of the other blocks in the frame.
In total, 12 N blocks ∑ t = 1 N f ∕ 2 N c t N s 2 N b 2 arithmetical operations are needed during the motion estimation step, where N c = 2 is the number of the best motion candidates N f = 7 is the number of frames, t is a time instant, N s = 24 size of the search window, N b is the size of the motion estimation block and Nblocks is the number of blocks in the frame.
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In other words, for each block B i in the frame F t) we search for the blocks in the frames F(t - N f ),..., F(t - 1), F(t + 1),..., F(t + N f ) which maximize the similarity measure between blocks.
The obtained four positions are interpolated in order to estimate the position of that block in the frame I t.
An important novelty is that we introduce a variable number of temporal candidate blocks used for denoising the block in the frame F t variable.
For each block in the frame F t), we perform a three-step search algorithm from [21] within some support region V t -1.
For each block in the frame F t), a motion estimation algorithm searches neighbouring frames for a certain number of candidate blocks most resembling the current block from F t).
By introducing the local noise standard deviation into threshold Dmax, we are taking into account the fact that even if we find a perfect match of the current block within the previous frame F(t - 1), it will differ from the current block in the frame F t), due to the noise.
The size of each block in the frame was considered to be 8 and was equally divided such that the size of each set of X and Y in the block was 4. Figures 5 and 6 show the effects of the quantization step (( Delta =raisebox{1ex}{$pi $} left/ raisebox{-1ex raisebox{-1ex.;to;raisebox{1ex}{$256$}right/ !raisebox{-1ex}{$16$}right. to on the BEraisebox{1exgnal-to-noise ratio (SNR), respectively.
c) The size of each block in the frame was considered to be 8 and was equally divided such that the size of each set of X and Y in the block was 4. d) Figures 5 and 6 show the effects of the quantization step (( Delta =raisebox{1ex}{$pi $} left/ raisebox{-1ex raisebox{-1ex.;to;raisebox{1ex}{$256$}right/ !raisebox{-1ex}{$16$}right. to on the BEraisebox{1exgnal-to-noise ratio (SNR), respectively.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com