Package gov.nih.mipav.model.algorithms

Class ImageQuality

  • All Implemented Interfaces:
    java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener
    public class ImageQuality
extends AlgorithmBase
    Author:
    aailb MIT License imageQualityIndex.m by Zhou Wang ported with his kind permission. The original source code for imageQualityIndex.m is Copyright (c) 2001 The University of Texas at Austin ssim_index.m and ssim.m by Zhou Wang ported with his kind permission. The original source code for ssim.index.m is Copyright(c) 2003 Zhou Wang The original source code for ssim.m is Copyright(c) 2009 Zhou Wang msssim.m and ssim_index.new.m by Zhou Wang ported with his kind permission. For VISUAL_INFORMATION_FIDELITY: % -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------ % Copyright (c) 2005 The University of Texas at Austin % All rights reserved. % % Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, % modify, and distribute this code (the source files) and its documentation for % any purpose, provided that the copyright notice in its entirety appear in all copies of this code, and the % original source of this code, Laboratory for Image and Video Engineering (LIVE, http://live.ece.utexas.edu) % at the University of Texas at Austin (UT Austin, % http://www.utexas.edu), is acknowledged in any publication that reports research using this code. The research % is to be cited in the bibliography as: % % H. R. Sheikh and A. C. Bovik, "Image Information and Visual Quality", IEEE Transactions on % Image Processing, (to appear). % % IN NO EVENT SHALL THE UNIVERSITY OF TEXAS AT AUSTIN BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, % OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OF THIS DATABASE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF TEXAS % AT AUSTIN HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. % % THE UNIVERSITY OF TEXAS AT AUSTIN SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, % AND THE UNIVERSITY OF TEXAS AT AUSTIN HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. % % -----------COPYRIGHT NOTICE ENDS WITH THIS LINE------------ % %This is an implementation of the algorithm for calculating the %Visual Information Fidelity (VIF) measure (may also be known as the Sheikh %-Bovik Index) between two images. Please refer %to the following paper: % %H. R. Sheikh and A. C. Bovik "Image Information and Visual Quality" %IEEE Transactios on Image Processing, in publication, May 2005. %Download manuscript draft from http://live.ece.utexas.edu in the %Publications link % %This implementation is slightly differnet from the one used to report %results in the paper above. The modification have to do with using more %subands than those used in the paper, better handling of image boundaries, %and a window that automatically resizes itself based on the scale. % %Report bugfixes and comments to hamid.sheikh@ieee.org % %---------------------------------------------------------------------- % Prerequisites: The Steerable Pyramid toolbox. Available at % http://www.cns.nyu.edu/~lcv/software.html % %Input : (1) img1: The reference image % (2) img2: The distorted image (order is important) % %Output: (1) VIF te visual information fidelity measure between the two images %Default Usage: % Given 2 test images img1 and img2, whose dynamic range is 0-255 % % vif = vifvec(img1, img2); % %Advanced Usage: % Users may want to modify the parameters in the code. % (1) Modify sigma_nsq to find tune for your image dataset. % (2) MxM is the block size that denotes the size of a vector used in the % GSM model. % (3) subbands included in the computation NQM is ported with the kind permission of Professor Brian L. Evans: Copyright (c) 1999-2021 The University of Texas at Austin All rights reserved. Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this software and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this software. IN NO EVENT SHALL THE UNIVERSITY OF TEXAS AT AUSTIN BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF TEXAS AT AUSTIN HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF TEXAS AT AUSTIN SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF TEXAS AT AUSTIN HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. VSR is ported with the kind permissions of Dr. Sheila S. Hemami and Professor Damon Chandler at Ritsumeikan University in Japan. They are the co_inventors of the method. Author: D. M. Chander Copyright 1998-2007 Image Coding and Analysis Lab, Oklahoma State University, Stillwater, OK 74078 USA. $Revision: BETA 1.02.0.0 $ $Date: 2007/10/04/ 15:00:00 $ For DWT code used for VSNR: //////////////////////////////////////////////////////////////////////////// // // // COPYRIGHT (c) 1998, 2002, VCL // // ------------------------------ // // Permission to use, copy, modify, distribute and sell this software // // and its documentation for any purpose is hereby granted without fee, // // provided that the above copyright notice appear in all copies and // // that both that copyright notice and this permission notice appear // // in supporting documentation. VCL makes no representations about // // the suitability of this software for any purpose. // // // // DISCLAIMER: // // ----------- // // The code provided hereunder is provided as is without warranty // // of any kind, either express or implied, including but not limited // // to the implied warranties of merchantability and fitness for a // // particular purpose. The author(s) shall in no event be liable for // // any damages whatsoever including direct, indirect, incidental, // // consequential, loss of business profits or special damages. // // // Other metrics are from full_ref.py, no_ref.py and utils.py by Andrew Khalel. full_ref.py, no_ref.py and utils.py are Copyright (c) 2018 Andrew Khalel Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ## Implemented metrics - [x] Mean Squared Error (MSE) - [x] Root Mean Squared Error (RMSE) - [x] Peak Signal-to-Noise Ratio (PSNR) [[1]](https://ieeexplore.ieee.org/abstract/document/1284395/) - [x] Structural Similarity Index (SSIM) [[1]](https://ieeexplore.ieee.org/abstract/document/1284395/) - [x] Universal Quality Image Index (UQI) [[2]](https://ieeexplore.ieee.org/document/995823/) - [x] Multi-scale Structural Similarity Index (MS-SSIM) [[3]](https://ieeexplore.ieee.org/abstract/document/1292216/) - [x] Erreur Relative Globale Adimensionnelle de Synthese (ERGAS) [[4]](https://hal.archives-ouvertes.fr/hal-00395027/) - [x] Spatial Correlation Coefficient (SCC) [[5]](https://www.tandfonline.com/doi/abs/10.1080/014311698215973) - [x] Relative Average Spectral Error (RASE) [[6]](https://ieeexplore.ieee.org/document/1304896/) - [x] Spectral Angle Mapper (SAM) [[7]](https://ntrs.nasa.gov/search.jsp?R=19940012238) - [x] Spectral Distortion Index (D_lambda) [[8]](https://www.ingentaconnect.com/content/asprs/pers/2008/00000074/00000002/art00003) - [x] Spatial Distortion Index (D_S) [[8]](https://www.ingentaconnect.com/content/asprs/pers/2008/00000074/00000002/art00003) - [x] Quality with No Reference (QNR) [[8]](https://www.ingentaconnect.com/content/asprs/pers/2008/00000074/00000002/art00003) - [x] Visual Information Fidelity (VIF) [[9]](https://ieeexplore.ieee.org/abstract/document/1576816/) - [x] Block Sensitive - Peak Signal-to-Noise Ratio (PSNR-B) [[10]](https://ieeexplore.ieee.org/abstract/document/5535179/) Available metrics list mse, rmse, psnr, rmse_sw, uqi, ssim, ergas, scc, rase, sam, msssim, vifp, psnrb ## References [1] "Image quality assessment: from error visibility to structural similarity." 2004)
    [2] "A universal image quality index." (2002)
    [3] "Multiscale structural similarity for image quality assessment." (2003)
    [4] "Quality of high resolution synthesised images: Is there a simple criterion?." (2000)
    [5] "A wavelet transform method to merge Landsat TM and SPOT panchromatic data." (1998)
    [6] "Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition." (2004)
    [7] "Discrimination among semi-arid landscape endmembers using the spectral angle mapper (SAM) algorithm." (1992)
    [8] "Multispectral and panchromatic data fusion assessment without reference." (2008)
    [9] "Image information and visual quality." (2006)
    [10] "Quality Assessment of Deblocked Images" (2011)

    • Field Detail

      • metrics

        private int[] metrics

      • results

        private double[] results

      • referenceImage

        private ModelImage referenceImage

      • PEAK_SIGNAL_TO_NOISE_RATIO

        public final int PEAK_SIGNAL_TO_NOISE_RATIO
        See Also:
        Constant Field Values

      • STRUCTURAL_SIMILARITY_INDEX

        public final int STRUCTURAL_SIMILARITY_INDEX
        See Also:
        Constant Field Values

      • SSIM_WITH_AUTOMATIC_DOWNSAMPLING

        public final int SSIM_WITH_AUTOMATIC_DOWNSAMPLING
        See Also:
        Constant Field Values

      • UNIVERSAL_QUALITY_IMAGE_INDEX

        public final int UNIVERSAL_QUALITY_IMAGE_INDEX
        See Also:
        Constant Field Values

      • MULTI_SCALE_STRUCTURAL_SIMILARITY_INDEX

        public final int MULTI_SCALE_STRUCTURAL_SIMILARITY_INDEX
        See Also:
        Constant Field Values

      • SPATIAL_CORRELATION_COEFFICIENT

        public final int SPATIAL_CORRELATION_COEFFICIENT
        See Also:
        Constant Field Values

      • RELATIVE_AVERAGE_SPECTRAL_ERROR

        public final int RELATIVE_AVERAGE_SPECTRAL_ERROR
        See Also:
        Constant Field Values

      • VISUAL_INFORMATION_FIDELITY

        public final int VISUAL_INFORMATION_FIDELITY
        See Also:
        Constant Field Values

      • PIXEL_BASED_VISUAL_INFORMATION_FIDELITY

        public final int PIXEL_BASED_VISUAL_INFORMATION_FIDELITY
        See Also:
        Constant Field Values

      • BLOCK_SENSITIVE_PEAK_SIGNAL_TO_NOISE_RATIO

        public final int BLOCK_SENSITIVE_PEAK_SIGNAL_TO_NOISE_RATIO
        See Also:
        Constant Field Values

      • testBuffer

        private double[] testBuffer

      • testRedBuffer

        private float[] testRedBuffer

      • testGreenBuffer

        private float[] testGreenBuffer

      • testBlueBuffer

        private float[] testBlueBuffer

      • referenceBuffer

        private double[] referenceBuffer

      • referenceRedBuffer

        private float[] referenceRedBuffer

      • referenceGreenBuffer

        private float[] referenceGreenBuffer

      • referenceBlueBuffer

        private float[] referenceBlueBuffer

      • testYBuffer

        private double[] testYBuffer

      • referenceYBuffer

        private double[] referenceYBuffer

      • rmse_sw_mean

        private double rmse_sw_mean

      • universalImageQualityIndex

        private double universalImageQualityIndex

      • structuralSimilarityIndex

        private double structuralSimilarityIndex

      • overall_mssim

        private double overall_mssim

      • sam_mean

        private double sam_mean

      • psnr_b

        private double psnr_b

      • length

        private int length

      • YCrCbRequired

        private boolean YCrCbRequired

      • isColor

        private boolean isColor

      • meanSquareError

        private double meanSquareError

      • meanRedSquareError

        private double meanRedSquareError

      • meanGreenSquareError

        private double meanGreenSquareError

      • meanBlueSquareError

        private double meanBlueSquareError

      • rootMeanSquareError

        private double rootMeanSquareError

      • peakSignalToNoiseRatio

        private double peakSignalToNoiseRatio

      • rmse_map

        private double[][] rmse_map

      • rmse_red_map

        private double[][] rmse_red_map

      • rmse_green_map

        private double[][] rmse_green_map

      • rmse_blue_map

        private double[][] rmse_blue_map

      • ergas_mean

        private double ergas_mean

      • spatialCorrelationCoefficient

        private double spatialCorrelationCoefficient

      • rase_mean

        private double rase_mean

      • vifp_mean

        private double vifp_mean

      • vif

        private double vif

      • nqm_value

        private double nqm_value

      • vsnr_value

        private double vsnr_value

      • nDims

        private int nDims

      • xDim

        private int xDim

      • yDim

        private int yDim

      • ws

        private int ws

      • k1

        private double k1

      • k2

        private double k2

      • sigma

        private double sigma

      • level

        private int level

      • weight

        private double[] weight

      • method

        private int method

      • r

        private double r

      • win

        private double[][] win

      • sigma_nsq

        private double sigma_nsq

      • subbands

        private int[] subbands

      • M

        private int M

      • VA

        private double VA

      • alpha

        private double alpha

      • vsnr_data_b

        private int vsnr_data_b

      • vsnr_data_k

        private double vsnr_data_k

      • vsnr_data_g

        private double vsnr_data_g

      • vsnr_data_r

        private double vsnr_data_r

      • vsnr_data_v

        private double vsnr_data_v

      • vsnr_data_num_levels

        private int vsnr_data_num_levels

      • vsnr_data_filter_gains

        private int[] vsnr_data_filter_gains

      • vsnr_data_fs

        private double[] vsnr_data_fs

      • vsnr_data_pix2lum_table

        private double[] vsnr_data_pix2lum_table

      • vsnr_data_CTe

        private double vsnr_data_CTe

      • vsnr_data_mX

        private double vsnr_data_mX

      • vsnr_data_mL

        private double vsnr_data_mL

      • vsnr_data_zeta

        private double vsnr_data_zeta

      • vsnr_data_Cis

        private double[] vsnr_data_Cis

      • vsnr_data_Ci

        private double vsnr_data_Ci

      • vsnr_data_Ce

        private double vsnr_data_Ce

      • GWAVELIFT_NORM_1_1

        boolean GWAVELIFT_NORM_1_1

    • Constructor Detail

      • ImageQuality

        public ImageQuality()

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    int ws,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    int ws,
                    double k1,
                    double k2,
                    double sigma,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    int ws,
                    double k1,
                    double k2,
                    double sigma,
                    int level,
                    double[] weight,
                    int method,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    int ws,
                    double r,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    int ws,
                    double[][] win,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    double sigma_nsq,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    double sigma_nsq,
                    int[] subbands,
                    int M,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    double VA,
                    int[] metrics,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    double alpha,
                    int vsnr_data_b,
                    double vsnr_data_k,
                    double vsnr_data_g,
                    double vsnr_data_r,
                    double vsnr_data_v,
                    int vsnr_data_num_levels,
                    int[] vsnr_data_filter_gains,
                    double[] results)

      • ImageQuality

        public ImageQuality​(ModelImage referenceImage,
                    ModelImage testImage,
                    int[] metrics,
                    int ws,
                    double k1,
                    double k2,
                    double sigma,
                    double r,
                    double[][] win,
                    double sigma_nsq,
                    int[] subbands,
                    int M,
                    int level,
                    double[] weight,
                    int method,
                    double VA,
                    double alpha,
                    int vsnr_data_b,
                    double vsnr_data_k,
                    double vsnr_data_g,
                    double vsnr_data_r,
                    double vsnr_data_v,
                    int vsnr_data_num_levels,
                    int[] vsnr_data_filter_gains,
                    double[] results)

    • Method Detail

      • testMse

        public void testMse()

      • testRmse

        public void testRmse()

      • testPsnr

        public void testPsnr()

      • testErgas

        public void testErgas()

      • testScc

        public void testScc()

      • testRase

        public void testRase()

      • testUqi

        public void testUqi()

      • testSsim

        public void testSsim()

      • testSsimDownload

        public void testSsimDownload()

      • testMsssim

        public void testMsssim()

      • testSam

        public void testSam()

      • testNQM

        public void testNQM()

      • testPSNRB

        public void testPSNRB()

      • testVIF

        public void testVIF()

      • testVIFP

        public void testVIFP()

      • testVSNR

        public void testVSNR()

      • runAlgorithm

        public void runAlgorithm()
        Description copied from class: AlgorithmBase
        Actually runs the algorithm. Implemented by inheriting algorithms.
        Specified by:
        runAlgorithm in class AlgorithmBase

      • mse

        private void mse()

      • rmse

        private void rmse()

      • psnr

        private void psnr()

      • copyMakeBorder

        public double[][] copyMakeBorder​(double[][] src,
                                 int top,
                                 int bottom,
                                 int left,
                                 int right,
                                 int borderType,
                                 double borderValue)

      • filter2Same

        private double[][] filter2Same​(double[][] img,
                               double[][] win)

      • correlationFilter

        private double[][] correlationFilter​(double[][] img)

      • uniformFilter

        private double[][] uniformFilter​(double[][] img,
                                 int size1,
                                 int size2)

      • rmse_sw

        private void rmse_sw()

      • filter2Valid

        private double[][] filter2Valid​(double[][] img,
                                double[][] filter)

      • ergas

        private void ergas()

      • scc

        private void scc()

      • rase

        private void rase()

      • uqi

        private void uqi()

      • msssim

        private void msssim()

      • ssim

        private void ssim​(boolean downSampling)

      • sam

        private void sam()

      • psnrb

        private void psnrb()

      • _compute_bef

        private double _compute_bef​(double[] im,
                            int block_size)

      • log2

        private double log2​(double input)

      • vifp

        private void vifp()

      • vifvec

        private void vifvec()

      • refparams_vecgsm

        private void refparams_vecgsm​(double[][][] ssarr,
                              double[][] l_arr,
                              java.util.Vector<double[][]> org)

      • filter2SameWithDownSample

        private double[][] filter2SameWithDownSample​(double[][] img,
                                             double[][] win,
                                             int borderType,
                                             int downSampleY,
                                             int downSampleX,
                                             int startY,
                                             int startX,
                                             int stopY,
                                             int stopX)

      • vifsub_est_M

        private void vifsub_est_M​(java.util.Vector<double[][]> g_all,
                          java.util.Vector<double[][]> vv_all,
                          java.util.Vector<double[][]> org,
                          java.util.Vector<double[][]> dist)

      • nqm

        private void nqm()

      • gthresh

        private double[] gthresh​(double[] x,
                         double T,
                         double[] z)

      • cmaskn

        private double[] cmaskn​(double[] c,
                        double[] ci,
                        double[] a,
                        double[] ai,
                        double i)

      • ctf

        private double ctf​(double f_r)

      • fftshift

        private double[][] fftshift​(double[][] in)

      • vsnr

        private void vsnr()

      • find_best_csnrs

        private double find_best_csnrs​(double Ce)

      • analyze_dst_img

        private double[] analyze_dst_img()

      • analyze_src_img

        private void analyze_src_img()

      • best_csnrs

        private double best_csnrs​(double v_idx)

      • imdwt

        private double[][][][] imdwt​(double[][] LL0,
                             int num_levels)

      • DoTransformRows

        public void DoTransformRows​(double[][] Buffer,
                            double[][] SBuffer,
                            double[][] DBuffer)

      • DoTransformCols

        public void DoTransformCols​(double[][] Buffer,
                            double[][] SBuffer,
                            double[][] DBuffer)

      • Reconstruct

        private void Reconstruct​(double[][][] bands,
                         int num_scales)

      • DoUntransformCols

        private void DoUntransformCols​(double[][] Buffer,
                               double[][] SBuffer,
                               double[][] DBuffer)

      • DoUntransformRows

        private void DoUntransformRows​(double[][] Buffer,
                               double[][] SBuffer,
                               double[][] DBuffer)