pyiqa.archs.nlpd_arch
=====================

.. py:module:: pyiqa.archs.nlpd_arch

.. autoapi-nested-parse::

   NLPD Metric

   @article{laparra2016nlpd,
     title={Perceptual image quality assessment using a normalized Laplacian pyramid},
     author={Laparra, Valero and Ball{\'e}, Johannes and Berardino, Alexander and Simoncelli, Eero P},
     journal={Electronic Imaging},
     volume={2016},
     number={16},
     pages={1--6},
     year={2016},
     publisher={Society for Imaging Science and Technology}
   }

   Created by: https://github.com/dingkeyan93/IQA-optimization/blob/master/IQA_pytorch/NLPD.py

   Modified by: Jiadi Mo (https://github.com/JiadiMo)

   Refer to:
       Matlab code from https://www.cns.nyu.edu/~lcv/NLPyr/NLP_dist.m;







Module Contents
---------------

.. py:data:: LAPLACIAN_FILTER

.. py:class:: NLPD(channels=1, test_y_channel=True, k=6, filt=None)

   Bases: :py:obj:`torch.nn.Module`


   Normalised lapalcian pyramid distance
   :param - channels: Number of channel expected to calculate.
   :param - test_y_channel: Boolean, whether to use y channel on ycbcr which mimics official matlab code.

   .. rubric:: References

   Laparra, Valero, Johannes Ballé, Alexander Berardino, and Eero P. Simoncelli.
   "Perceptual image quality assessment using a normalized Laplacian pyramid."
   Electronic Imaging 2016, no. 16 (2016): 1-6.


   .. py:method:: DN_filters()

      Define parameters for the divisive normalization



   .. py:method:: pyramid(im)

      Compute Laplacian Pyramid
      :param im: An input tensor. Shape :math:`(N, C, H, W)`.



   .. py:method:: nlpd(x1, x2)

      Compute Normalised lapalcian pyramid distance for a batch of images.
      :param x1: An input tensor. Shape :math:`(N, C, H, W)`.
      :param x2: A target tensor. Shape :math:`(N, C, H, W)`.

      :returns: Index of similarity between two images. Usually in [0, 1] interval.



   .. py:method:: forward(X, Y)

      Computation of NLPD metric.
      :param X: An input tensor. Shape :math:`(N, C, H, W)`.
      :param Y: A target tensor. Shape :math:`(N, C, H, W)`.

      :returns: Value of NLPD metric in [0, 1] range.