NR_PWN

NR_PWN

This work proposes a perceptual based No-reference perceptually weighted noise (NR_PWN) metric by integrating perceptually weighted local noise into a probability summation model. Unlike existing objective metrics, the proposed no-reference metric is able to predict the relative amount of noise perceived in images with different content. Results are reported on both the LIVE and TID2008 databases. The proposed no-reference metric achieves consistently a good performance across noise types and across databases as compared to many of the best very recent no-reference quality metrics.

Contact

Lina Karam ([email protected]) and Tong Zhu ([email protected])
IVU Lab, http://ivulab.asu.edu/
Reference:
Tong Zhu and Lina Karam. “A no-reference objective image quality metric based on perceptually weighted local noise.” EURASIP Journal on Image and Video Processing 2014.1 (2014): 1-8.
The provided FR_PWN (full-reference perceptually weighted noise metric) and NR_PWN (No-reference perceptually weighted noise metric) Software is implemented in Matlab2012b. See Copyright Notice, Usage Conditions, and Disclaimer at the end of this file.

Usage

compute_FR_PWN.m computes the FR_PWN (Full-reference perceptually weighted noise metric) given an input distorted grayscale image and an input reference grayscale image.

I=im2double(rgb2gray(imread(distorted_image_name)));
I_ref=im2double(rgb2gray(imread(reference_image_name)));
FR_PWN_metric=compute_FR_PWN(I,I_ref)

compute_NR_PWN.m computes the NR_PWN (No-reference perceptually weighted noise metric) given an input distorted grayscale image.

I=im2double(rgb2gray(imread(distorted_image_name)));
NR_PWN_metric=compute_NR_PWN(I)

Test Demo

Download the Test_Image_Set.zip from the same webpage of this code. Unzip these image set and put in the same directory with the code.
Four demo are provided to demonstrated the result presented in the paper.
Tong Zhu and Lina Karam. and Lina Karam. "A no-reference objective image quality metric based on perceptually weighted local noise." EURASIP Journal on Image and Video Processing 2014.1 (2014): 1-8.

To run FR_PWN on LIVE database white noise, use demo_FR_LIVE.m
To run NR_PWN on LIVE database white noise, use demo_NR_LIVE.m
To run FR_PWN on TID2008 database distortion type 1 and 5, use demo_FR_TID2008.m
To run NR_PWN on TID2008 database distortion type 1 and 5, use demo_NR_TID2008.m

Copyright

 Copyright (c) 2015-2016 Arizona Board of Regents.  All Rights Reserved.
 Contact: Lina Karam ([email protected]) and Tong Zhu ([email protected])
 Image, Video, and Usabilty (IVU) Lab, http://ivulab.asu.edu , Arizona State University
 This copyright statement may not be removed from any file containing it or from modifications to these files.
 This copyright notice must also be included in any file or product that is derived from the source files.
 
 Redistribution and use of this code in source and binary forms,  with or without modification, are permitted provided that the
 following conditions are met: 
 - Redistribution's of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
 - Redistribution's in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer
in the documentation and/or other materials provided with the distribution.
 - The Image, Video, and Usability Laboratory (IVU Lab, http://ivulab.asu.edu) is acknowledged in any publication that
 reports research results using this code, copies of this code, or modifications of this code. 
 The code and our papers are to be cited in the bibliography as:
Tong Zhu and Lina Karam. "A no-reference objective image quality metric based on perceptually weighted local noise." EURASIP Journal on Image and Video Processing 2014.1 (2014): 1-8.
 DISCLAIMER:
 This software is provided by the copyright holders and contributors "as is" and any express or implied warranties,
including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed.
In no event shall the Arizona Board of Regents, Arizona State University, IVU Lab members, authors or contributors be liable for
any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute
goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in
contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised
of the possibility of such damage.

Download

Download NR_PWN Software Package
Download Test Image Set
The test image set contains: LIVE Test Image Set (white noise) and TID2008 Test Image Set (Distortion type 1 and 5) (LIVE Copyright Notice) and (TID2008 Copyright Notice)