java.lang.Object
- java.lang.Thread
- - gov.nih.mipav.model.algorithms.AlgorithmBase
  - - gov.nih.mipav.model.algorithms.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)

Nested Class Summary
- Nested classes/interfaces inherited from class java.lang.Thread
  java.lang.Thread.State, java.lang.Thread.UncaughtExceptionHandler

Field Summary

Fields
Modifier and Type	Field	Description
`private double`	`alpha`
`(package private) static double`	`ALPHA`
`(package private) static double`	`BETA`
`int`	`BLOCK_SENSITIVE_PEAK_SIGNAL_TO_NOISE_RATIO`
`int`	`BORDER_CONSTANT`
`int`	`BORDER_DEFAULT`
`int`	`BORDER_REFLECT`
`int`	`BORDER_REFLECT_101`
`int`	`BORDER_REPLICATE`
`int`	`BORDER_WRAP`
`private ModelImage`	`clr`
`private ModelImage`	`clr_const`
`private ModelImage`	`clr_noise`
`(package private) static double`	`DELTA`
`int`	`ERGAS`
`private double`	`ergas_mean`
`(package private) static double`	`GAMMA`
`private ModelImage`	`gry`
`private ModelImage`	`gry_const`
`private ModelImage`	`gry_noise`
`(package private) boolean`	`GWAVELIFT_NORM_1_1`
`private boolean`	`isColor`
`private double`	`k1`
`private double`	`k2`
`private int`	`length`
`private int`	`level`
`private int`	`M`
`int`	`MEAN_SQUARED_ERROR`
`private double`	`meanBlueSquareError`
`private double`	`meanGreenSquareError`
`private double`	`meanRedSquareError`
`private double`	`meanSquareError`
`private int`	`method`
`private int[]`	`metrics`
`int`	`MULTI_SCALE_STRUCTURAL_SIMILARITY_INDEX`
`private int`	`nDims`
`int`	`NQM`
`private double`	`nqm_value`
`private double`	`overall_mssim`
`int`	`PEAK_SIGNAL_TO_NOISE_RATIO`
`private double`	`peakSignalToNoiseRatio`
`int`	`PIXEL_BASED_VISUAL_INFORMATION_FIDELITY`
`private static int`	`PRODUCT`
`private double`	`psnr_b`
`private double`	`r`
`private double`	`rase_mean`
`private float[]`	`referenceBlueBuffer`
`private double[]`	`referenceBuffer`
`private float[]`	`referenceGreenBuffer`
`private ModelImage`	`referenceImage`
`private float[]`	`referenceRedBuffer`
`private double[]`	`referenceYBuffer`
`int`	`RELATIVE_AVERAGE_SPECTRAL_ERROR`
`private double[]`	`results`
`private double[][]`	`rmse_blue_map`
`private double[][]`	`rmse_green_map`
`private double[][]`	`rmse_map`
`private double[][]`	`rmse_red_map`
`int`	`RMSE_SW`
`private double`	`rmse_sw_mean`
`int`	`ROOT_MEAN_SQUARED_ERROR`
`private double`	`rootMeanSquareError`
`private double`	`sam_mean`
`private double`	`sigma`
`private double`	`sigma_nsq`
`int`	`SPATIAL_CORRELATION_COEFFICIENT`
`private double`	`spatialCorrelationCoefficient`
`int`	`SPECTRAL_ANGLE_MAPPER`
`int`	`SSIM_WITH_AUTOMATIC_DOWNSAMPLING`
`int`	`STRUCTURAL_SIMILARITY_INDEX`
`private double`	`structuralSimilarityIndex`
`private int[]`	`subbands`
`private float[]`	`testBlueBuffer`
`private double[]`	`testBuffer`
`private float[]`	`testGreenBuffer`
`private ModelImage`	`testImage`
`private float[]`	`testRedBuffer`
`private double[]`	`testYBuffer`
`(package private) static double`	`TWOALPHA`
`(package private) static double`	`TWOBETA`
`(package private) static double`	`TWODELTA`
`(package private) static double`	`TWOGAMMA`
`private ViewUserInterface`	`UI`
`int`	`UNIVERSAL_QUALITY_IMAGE_INDEX`
`private double`	`universalImageQualityIndex`
`private double`	`VA`
`private double`	`vif`
`private double`	`vifp_mean`
`int`	`VISUAL_INFORMATION_FIDELITY`
`int`	`VSNR`
`private int`	`vsnr_data_b`
`private double`	`vsnr_data_Ce`
`private double`	`vsnr_data_Ci`
`private double[]`	`vsnr_data_Cis`
`private double`	`vsnr_data_CTe`
`private int[]`	`vsnr_data_filter_gains`
`private double[]`	`vsnr_data_fs`
`private double`	`vsnr_data_g`
`private double`	`vsnr_data_k`
`private double`	`vsnr_data_mL`
`private double`	`vsnr_data_mX`
`private int`	`vsnr_data_num_levels`
`private double[]`	`vsnr_data_pix2lum_table`
`private double`	`vsnr_data_r`
`private double`	`vsnr_data_v`
`private double`	`vsnr_data_zeta`
`private double`	`vsnr_value`
`private double[]`	`weight`
`private double[][]`	`win`
`private int`	`ws`
`private static int`	`WTD_SUM`
`private int`	`xDim`
`private boolean`	`YCrCbRequired`
`private int`	`yDim`

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase
destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread
MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors
Constructor	Description
`ImageQuality()`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, double VA, int[] metrics, double[] results)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, double[] results)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, double sigma_nsq, double[] results)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, double sigma_nsq, int[] subbands, int M, double[] results)`
`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(ModelImage referenceImage, ModelImage testImage, int[] metrics, int ws, double[] results)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, int ws, double[][] win, double[] results)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, int ws, double r, double[] results)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, int ws, double k1, double k2, double sigma, double[] results)`
`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)`
`ImageQuality(ModelImage referenceImage, ModelImage testImage, int[] metrics, int ws, double k1, double k2, double sigma, int level, double[] weight, int method, double[] results)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`private double`	`_compute_bef(double[] im, int block_size)`
`private double[]`	`analyze_dst_img()`
`private void`	`analyze_src_img()`
`private double`	`best_csnrs(double v_idx)`
`private double[]`	`cmaskn(double[] c, double[] ci, double[] a, double[] ai, double i)`
`double[][]`	`copyMakeBorder(double[][] src, int top, int bottom, int left, int right, int borderType, double borderValue)`
`private double[][]`	`correlationFilter(double[][] img)`
`private double`	`ctf(double f_r)`
`void`	`DoTransformCols(double[][] Buffer, double[][] SBuffer, double[][] DBuffer)`
`void`	`DoTransformRows(double[][] Buffer, double[][] SBuffer, double[][] DBuffer)`
`private void`	`DoUntransformCols(double[][] Buffer, double[][] SBuffer, double[][] DBuffer)`
`private void`	`DoUntransformRows(double[][] Buffer, double[][] SBuffer, double[][] DBuffer)`
`private void`	`ergas()`
`private double[][]`	`fftshift(double[][] in)`
`private double[][]`	`filter2Same(double[][] img, double[][] win)`
`private double[][]`	`filter2SameWithDownSample(double[][] img, double[][] win, int borderType, int downSampleY, int downSampleX, int startY, int startX, int stopY, int stopX)`
`private double[][]`	`filter2Valid(double[][] img, double[][] filter)`
`private double`	`find_best_csnrs(double Ce)`
`private double[]`	`gthresh(double[] x, double T, double[] z)`
`private double[][][][]`	`imdwt(double[][] LL0, int num_levels)`
`private double`	`log2(double input)`
`private void`	`mse()`
`private void`	`msssim()`
`private void`	`nqm()`
`private void`	`psnr()`
`private void`	`psnrb()`
`private void`	`rase()`
`private void`	`Reconstruct(double[][][] bands, int num_scales)`
`private void`	`refparams_vecgsm(double[][][] ssarr, double[][] l_arr, java.util.Vector<double[][]> org)`
`private void`	`rmse()`
`private void`	`rmse_sw()`
`void`	`runAlgorithm()`	Actually runs the algorithm.
`private void`	`sam()`
`private void`	`scc()`
`private void`	`ssim(boolean downSampling)`
`void`	`testErgas()`
`void`	`testMse()`
`void`	`testMsssim()`
`void`	`testNQM()`
`void`	`testPsnr()`
`void`	`testPSNRB()`
`void`	`testRase()`
`void`	`testRmse()`
`void`	`testSam()`
`void`	`testScc()`
`void`	`testSsim()`
`void`	`testSsimDownload()`
`void`	`testUqi()`
`void`	`testVIF()`
`void`	`testVIFP()`
`void`	`testVSNR()`
`private double[][]`	`uniformFilter(double[][] img, int size1, int size2)`
`private void`	`uqi()`
`private void`	`vifp()`
`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)`
`private void`	`vifvec()`
`private void`	`vsnr()`

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase
actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread
activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, join, join, join, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, suspend, toString, yield

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

UI
```
private ViewUserInterface UI
```

metrics
```
private int[] metrics
```

results
```
private double[] results
```

referenceImage
```
private ModelImage referenceImage
```

testImage
```
private ModelImage testImage
```

MEAN_SQUARED_ERROR
```
public final int MEAN_SQUARED_ERROR
```
See Also:

Constant Field Values

ROOT_MEAN_SQUARED_ERROR
```
public final int ROOT_MEAN_SQUARED_ERROR
```
See Also:

Constant Field Values

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

ERGAS
```
public final int ERGAS
```
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

SPECTRAL_ANGLE_MAPPER
```
public final int SPECTRAL_ANGLE_MAPPER
```
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

RMSE_SW
```
public final int RMSE_SW
```
See Also:

Constant Field Values

NQM
```
public final int NQM
```
See Also:

Constant Field Values

VSNR
```
public final int VSNR
```
See Also:

Constant Field Values

PRODUCT
```
private static final int PRODUCT
```
See Also:

Constant Field Values

WTD_SUM
```
private static final int WTD_SUM
```
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
```

gry
```
private ModelImage gry
```

gry_noise
```
private ModelImage gry_noise
```

gry_const
```
private ModelImage gry_const
```

clr
```
private ModelImage clr
```

clr_noise
```
private ModelImage clr_noise
```

clr_const
```
private ModelImage clr_const
```

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
```

BORDER_CONSTANT
```
public final int BORDER_CONSTANT
```
See Also:

Constant Field Values

BORDER_REPLICATE
```
public final int BORDER_REPLICATE
```
See Also:

Constant Field Values

BORDER_REFLECT
```
public final int BORDER_REFLECT
```
See Also:

Constant Field Values

BORDER_WRAP
```
public final int BORDER_WRAP
```
See Also:

Constant Field Values

BORDER_REFLECT_101
```
public final int BORDER_REFLECT_101
```
See Also:

Constant Field Values

BORDER_DEFAULT
```
public final int BORDER_DEFAULT
```
See Also:

Constant Field Values

ALPHA
```
static final double ALPHA
```
See Also:

Constant Field Values

BETA
```
static final double BETA
```
See Also:

Constant Field Values

GAMMA
```
static final double GAMMA
```
See Also:

Constant Field Values

DELTA
```
static final double DELTA
```
See Also:

Constant Field Values

TWOALPHA
```
static final double TWOALPHA
```
See Also:

Constant Field Values

TWOBETA
```
static final double TWOBETA
```
See Also:

Constant Field Values

TWOGAMMA
```
static final double TWOGAMMA
```
See Also:

Constant Field Values

TWODELTA
```
static final double TWODELTA
```
See Also:

Constant Field Values

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)

Class ImageQuality

Nested Class Summary

Nested classes/interfaces inherited from class java.lang.Thread

Field Summary

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

Fields inherited from class java.lang.Thread

Constructor Summary

Method Summary

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

Methods inherited from class java.lang.Thread

Methods inherited from class java.lang.Object

Field Detail

UI

metrics

results

referenceImage

testImage

MEAN_SQUARED_ERROR

ROOT_MEAN_SQUARED_ERROR

PEAK_SIGNAL_TO_NOISE_RATIO

STRUCTURAL_SIMILARITY_INDEX

SSIM_WITH_AUTOMATIC_DOWNSAMPLING

UNIVERSAL_QUALITY_IMAGE_INDEX

MULTI_SCALE_STRUCTURAL_SIMILARITY_INDEX

ERGAS

SPATIAL_CORRELATION_COEFFICIENT

RELATIVE_AVERAGE_SPECTRAL_ERROR

SPECTRAL_ANGLE_MAPPER

VISUAL_INFORMATION_FIDELITY

PIXEL_BASED_VISUAL_INFORMATION_FIDELITY

BLOCK_SENSITIVE_PEAK_SIGNAL_TO_NOISE_RATIO

RMSE_SW

NQM

VSNR

PRODUCT

WTD_SUM

testBuffer

testRedBuffer

testGreenBuffer

testBlueBuffer

referenceBuffer

referenceRedBuffer

referenceGreenBuffer

referenceBlueBuffer

testYBuffer

referenceYBuffer

rmse_sw_mean

universalImageQualityIndex

structuralSimilarityIndex

overall_mssim

sam_mean

psnr_b

length

YCrCbRequired

isColor

meanSquareError

meanRedSquareError

meanGreenSquareError

meanBlueSquareError

rootMeanSquareError

peakSignalToNoiseRatio

rmse_map

rmse_red_map

rmse_green_map

rmse_blue_map

ergas_mean

spatialCorrelationCoefficient

rase_mean

vifp_mean

vif

nqm_value

vsnr_value

gry

gry_noise

gry_const

clr

clr_noise

clr_const

nDims

xDim