Question about loss function

[parkjh688]

Hi.
I'm reading the paper and can't understand some part of loss function.
So I have questions about loss function code.

(1) Why didn't you add eps?
y_lum_lin = tf.nn.conv2d(tf.exp(y)-eps, lum_kernel, [1, 1, 1, 1], padding='SAME')

(2) Why did you tf.log twice to y_lum?
y_lum_ = tf.log(y_lum_lin_ + eps)
y_lum = tf.log(y_lum_lin + eps)
x_lum = tf.log(x_lum_lin + eps)

[gabrieleilertsen]

Hi. Without exactly remembering all the details, I think this is why:

1. I usually add some small constant eps when going to the log domain, i.e. x_log = log(x+eps), which would mean that when going back to linear from log you would do x = exp(x_log) - eps

2. The notation with '' at the end is for the ground truth, so that y and y_lum_lin_ corresponds to the ground truth image and luminance, respectively. y and y_lum_lin, on the other hand, refers to the reconstructed image and luminance, predicted by the network.