Peak Signal-to-Noise Ratio (PSNR) function.
tf.keras.ops.psnr(
x1, x2, max_val
)
This function computes the Peak Signal-to-Noise Ratio between two signals,
x1 and x2. PSNR is a measure of the quality of a reconstructed signal.
The higher the PSNR, the closer the reconstructed signal is to the original
signal. Note that it can become negative when the signal power is
smaller that the noise power.
Args |
|---|
x1
|
The first input signal.
|
x2
|
The second input signal. Must have the same shape as x1.
|
max_val
|
The maximum possible value in the signals.
|
Returns |
|---|
float
|
The PSNR value between x1 and x2.
|
Examples:
x1 = keras.random.normal((2, 4, 4, 3))
x2 = keras.random.normal((2, 4, 4, 3))
max_val = 1.0
keras.ops.nn.psnr(x1, x2, max_val)
-3.1697404
View source on GitHub