1.psnr
在超分辨率问题中，有一指标PSNR（信噪比）衡量重建图像的质量。
MSE为均方误差
K为图像对应的二进制位数，一般都是8（255位）
2.SRGAN原理
代码地址：https://github.com/aitorzip/PyTorch-SRGAN
1）网络结构：
class Generator(nn.Module):
def __init__(self, n_residual_blocks, upsample_factor):
super(Generator, self).__init__()
self.n_residual_blocks = n_residual_blocks
self.upsample_factor = upsample_factor
self.conv1 = nn.Conv2d(3, 64, 9, stride=1, padding=4)
for i in range(self.n_residual_blocks):
self.add_module('residual_block' + str(i+1), residualBlock())
self.conv2 = nn.Conv2d(64, 64, 3, stride=1, padding=1)
self.bn2 = nn.BatchNorm2d(64)
for i in range(self.upsample_factor/2):
self.add_module('upsample' + str(i+1), upsampleBlock(64, 256))
self.conv3 = nn.Conv2d(64, 3, 9, stride=1, padding=4)
def forward(self, x):
x = swish(self.conv1(x))
y = x.clone()
for i in range(self.n_residual_blocks):
y = self.__getattr__('residual_block' + str(i+1))(y)
x = self.bn2(self.conv2(y)) + x
for i in range(self.upsample_factor/2):
x = self.__getattr__('upsample' + str(i+1))(x)
return self.conv3(x)
有一sub-pixel Convolution操作
2）损失函数
1.内容损失函数，把某一层特征图的逐像素损失作为了内容损失，学一些高层的语义特征和结构信息。
2）对抗损失
3）正则损失
