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

Calculating PSNR MSE SSIM using MATLAB Image Processing By Using Matlab. Low pass filters for images using Matlab - Duration. How to calculate RMSE through Matlab - Duration: 4:46. When comparing compression codec’s it is used as an approximation to human perception of reconstruction quality, therefore in some cases one reconstruction may appear to be closer to the original than another, even though it has a lower PSNR (a higher PSNR would normally indicate that the reconstruction is of higher quality). Semakin mirip kedua citra maka nilai MSE dan RMSE nya semakin mendekati nilai nol. Sedangkan pada PSNR, dua buah citra dikatakan memiliki tingkat kemiripan yang rendah jika nilai PSNR di bawah 30 dB. Berikut ini merupakan contoh pemrograman GUI matlab untuk menghitung nilai MSE, RMSE, dan PSNR.

You are getting 3 PSNR values because your 'input.png' and 'groundTruth.png' are 3 channel RGB images and your code is calculating PSNR for each channel individually. You can convert your RGB image to grayscale before PSNR calculation to solve this issue. After this, I tried calculate the PSNR value with original image and stego image. 100 character which is read from file is embedded into image, higher PSNR value. 5 character, less PSNR value. That's why I get confused.-HERE is my PSNR 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.

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:

Psnr Image

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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');

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Psnr Calculation In Matlab For Machine Learning

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 Student

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.

Psnr Calculation In Matlab For Mac Pdf

Database	Results	Nonlinear fitting code	SROCC	KROCC	PLCC	RMSE
TID2008	PSNROnTID	NonlinearFittingTID	0.5531	0.4027	0.5734	1.0994
CSIQ	PSNROnCSIQ	NonlinearFittingCSIQ	0.8058	0.6084	0.8000	0.1575
LIVE	PSNROnLIVE	NonlinearFittingLIVE	0.8756	0.6865	0.8723	13.3597
IVC	NonlinearFittingIVC	0.6884	0.5218	0.7196	0.8460
Toyama-MICT	0.6132	0.4443	0.6429	0.9585
A57	0.6189	0.4309	0.7073	0.1737
WIQ	0.6257	0.4626	0.7939	14.1381
Weighted-Average	0.6874	0.5161	0.7020

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

Last update: Aug. 04, 2011