/TensorFlow 2.4


Returns the Peak Signal-to-Noise Ratio between a and b.

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].


# 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.
a First set of images.
b Second set of images.
max_val The dynamic range of the images (i.e., the difference between the maximum the and minimum allowed values).
name Namespace to embed the computation in.
The scalar PSNR between a and b. The returned tensor has type tf.float32 and shape [batch_size, 1].

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.