tf.image.psnr

tf.image.psnr(a,b,max_val,name=None)

Defined in tensorflow/python/ops/image_ops_impl.py.

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].

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.

Arguments:

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.

Returns:

The scalar PSNR between a and b. The returned tensor has type tf.float32 and shape [batch_size, 1].

https://tensorflow.google.cn/api_docs/python/tf/image/psnr?hl=zh-cn