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Returns the Peak Signal-to-Noise Ratio between a and b.
tf.image.psnr(
a, b, max_val, name=None
)
This is intended to be used on signals (or images). Produces a PSNR value for each image in batch.
The last three dimensions of input are expected to be [height, width, depth].
Example:
# Read images from file.
im1 = tf.decode_png('path/to/im1.png')
im2 = tf.decode_png('path/to/im2.png')
# Compute PSNR over tf.uint8 Tensors.
psnr1 = tf.image.psnr(im1, im2, max_val=255)
# Compute PSNR over tf.float32 Tensors.
im1 = tf.image.convert_image_dtype(im1, tf.float32)
im2 = tf.image.convert_image_dtype(im2, tf.float32)
psnr2 = tf.image.psnr(im1, im2, max_val=1.0)
# psnr1 and psnr2 both have type tf.float32 and are almost equal.
Returns | |
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The scalar PSNR between a and b. The returned tensor has type tf.float32
and shape [batch_size, 1].
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