## 3 Methodology
### Decoder  
As shown in Figure 4, the work in this paper adopted a triple-branch structure in the decoder for the first time, where the left and right branches represent the feature decoding process of T2 and T1, respectively, and the middle branch represents the feature fusion of T2 and T1.  
(1) Left and right branches: The left and right branches of the decoder each included five stages. In the former four stages, each one consisted of an MFE module and a concatenation operation. The last stage was composed of three parts, namely the MFE, \(1\times 1\) convolution, and the upsampling operation. Taking the left branch as an example, the feature \(X_{B}^{5}\) generated from the last stage of the encoder was put into the MFE module to produce a feature, represented by \(Y_{B}^{5}\). In addition, to better integrate the multilevel features and fuse the local features with multiscale contextual information, a skip connection was built, located between the encoder and decoder, that is, for \(X_{B}^{5}\) and \(Y_{B}^{5}\) after upsampling to perform concatenation operation along the channel dimension, and we denote the obtained features by \(D_{B}^{5}\). The concrete process of the first 4 stages is shown as follows:  
\[Y_{B}^{i}=MFE\Big{(}X_{B}^{i}\Big{)}. \tag{1}\]  
\[D_{B}^{i}=Concat\Big{(}X_{B}^{i-1},Upsample\Big{(}Y_{B}^{i}\Big{)}\Big{)},i=5,4,3,2. \tag{2}\]  
In the last stage, \(D_{B}^{2}\) went through an MFE, after which the output features underwent a \(1\times 1\) convolution for channel dimension reduction; finally, the feature map size was recovered to be in accordance with the raw image employing a bilinear interpolation upsampling operation.  
\begin{table}
\begin{tabular}{c c c c} \hline - & \(i\) & **Output Size** & **f** \\ \hline Encoder & 1 & 64 \(\times\) 64 \(\times\) 64 & 64 \(\times\) 64 \(\times\) 64 \\  & 2 & 256 \(\times\) 64 \(\times\) 64 & 128 \(\times\) 64 \(\times\) 64 \\  & 3 & 512 \(\times\) 32 \(\times\) 32 & 256 \(\times\) 32 \(\times\) 32 \\  & 4 & 1024 \(\times\) 16 \(\times\) 16 & 512 \(\times\) 16 \(\times\) 16 \\  & 5 & 2048 \(\times\) 8 \(\times\) 8 & 1024 \(\times\) 8 \(\times\) 8 \\ \hline \end{tabular}
\end{table}
Table 1: Encoder output feature size for each stage.  
Figure 3: The structure of the encoder.  
(2) Middle branch: Similarly, the middle branch was divided into 5 stages, the first 4 of which were the same, each of which contained an MFE, TA, and a concatenation operation. The last stage was the same as the left and right branches. In the first four stages, taking the first stage as an example, the two-branch fusion feature \(f_{5}\) generated by CAC from the encoder last stage passed through an MFE block, and the feature was represented by \(D_{F}^{5}\). Together with the output \(Y_{A}^{5}\) and \(Y_{B}^{5}\) of the same stage of the left and right branches, they were first upsampled and then sent to a TA block to fuse three-branch features. Finally, the \(f_{4}\) from the encoder performed a concatenation operation with the three-branch fused features through a skip connection for the purpose of combining local and more global information. The first 4 stages of the process are specified as follows:  
\[D_{F}^{i}=MFE(f_{i}), \tag{3}\]  
Figure 4: The structure of the decoder.  
\[D_{F}^{i}=TA\Big{(}Upsample\Big{(}Y_{A}^{i}\Big{)},Upsample\Big{(}Y_{B}^{i} \Big{)},Upsample\Big{(}D_{F}^{i}\Big{)}\Big{)}, \tag{4}\]  
\[D^{i}=Concat\Big{(}f_{i-1},D_{F}^{i}\Big{)},i=5,4,3,2. \tag{5}\]  
The feature maps' sizes from every stage in the decoder are shown in Table 2.