- Python Psnr
- Matlab For Mac Os X
- Psnr Calculation In Matlab For Mac Pdf
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How to calculate PSNR value? Learn more about image processing, psnr, wavelet transfrom, lifting wavelet transform Image Acquisition Toolbox, Image Processing Toolbox. The psnr function implements the following equation to calculate the Peak Signal-to-Noise Ratio (PSNR): P S N R = 10 log 10 ( p e a k v a l 2 / M S E ) where peakval is either specified by the user or taken from the range of the image datatype (e.g. For uint8 image it is 255 ).
Evaluation of PSNR Lin Zhang, Dept. Computing, The Hong Kong Polytechnic University |
Introduction
PSNR (Peak Singal-to-Noise Ratio) index is a traditional IQA metric.
Source Code
We used the PSNR implementation provided by Dr. Zhou Wang, which can be downloaded here https://ece.uwaterloo.ca/~z70wang/research/iwssim/psnr_mse.m.
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Usage Notes
1. This implementation can only deal with gray-scale images. So, you need to convert the RGB image to the grayscale version, which can be accomplished by rgb2gray in Matlab.
Evaluation Results
The results (in Matlab .mat format) are provided here. Each result file contains a n by 2 matrix, where n denotes the number of distorted images in the database. The first column is the PSNR values, and the second column is the mos/dmos values provided by the database. For example, you can use the following matlab code to calculate the SROCC and KROCC values for PSNR values obtained on the TID2008 database:
Python Psnr
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matData = load('PSNROnTID.mat');
PSNROnTID= matData.PSNROnTID;
PSNR_TID_SROCC = corr(PSNROnTID(:,1), PSNROnTID(:,2), 'type', 'spearman');
PSNR_TID_KROCC = corr(PSNROnTID(:,1), PSNROnTID(:,2), 'type', 'kendall');
PSNROnTID= matData.PSNROnTID;
PSNR_TID_SROCC = corr(PSNROnTID(:,1), PSNROnTID(:,2), 'type', 'spearman');
PSNR_TID_KROCC = corr(PSNROnTID(:,1), PSNROnTID(:,2), 'type', 'kendall');
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The source codes to calculate the PLCC and RMSE are also provided for each database. This needs a nonlinear regression procedure which is dependant on the initialization of the parameters. We try to adjust the parameters to get a high PLCC value. For different databases, the parameter initialization may be different. The nonlinear fitting function is of the form as described in [1].
Matlab For Mac Os X
Evaluation results of PSNR on seven databases are given below. Besides, for each evaluation metric, we present its weighted-average value over all the testing datasets; and the weight for each database is set as the number of distorted images in that dataset.
Reference
[1] H.R. Sheikh, M.F. Sabir, and A.C. Bovik, 'A statistical evaluation of recent full reference image quality assessment algorithms', IEEE Trans. on Image Processing, vol. 15, no. 11, pp. 3440-3451, 2006.
Created on: May. 08, 2011
Psnr Calculation In Matlab For Mac Pdf
Last update: Aug. 04, 2011