tf.image.psnr

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

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.image.psnr

Used in the notebooks

Used in the tutorials

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.

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].