Laser & Optoelectronics Progress, Volume. 56, Issue 3, 031009(2019)
Color Image Quality Assessment Based on Quaternion Spectral Residual
Figures & Tables(10)
Fig. 2. Quaternion gradient maps of color images. (a) Color images; (b) corresponding quaternion gradient maps of (a); (c) color images; (d) corresponding quaternion gradient maps of (c)
Fig. 4. Regression curves of different image quality evaluation algorithms in TID2013. (a) SSIM; (b) FISM; (c) MS-GMSDc; (d) QSSIM; (e) SR-SIM; (f) QSR-SIM
Fig. 5. Reference image and its distortion images of different types. (a) Reference image I07; (b) I07_11_5; (c) I07_12_4; (d) I07_15_3; (e) I07_17_4; (f) I07_24_5
Table 1. Results of five kinds of distorted pictures of reference image I07 in different evaluation algorithm experiments
View tableTable 1. Results of five kinds of distorted pictures of reference image I07 in different evaluation algorithm experiments
Algorithm I07_11_5 I07_12_4 I07_15_3 I07_17_4 I07_24_5 Subjective score 0.9773 2.8636 3.0455 6.7273 0.4762 QSR-SIM 0.9701 0.9919 0.9968 0.9976 0.9691 VSI[ 4 ]0.8964 0.9610 0.9614 0.9868 0.8875 SR-SIM[ 3 ]0.8283 0.9317 0.9636 0.9803 0.8056 FSIM[ 5 ]0.7203 0.9150 0.9610 0.9621 0.7137 SSIM[ 21 ]0.5922 0.7208 0.9683 0.9516 0.6019 VSNR[ 23 ]8.7561 15.0237 12.223 11.3239 8.6929 PSNR[ 24 ]23.0007 26.1743 27.2014 25.0836 23.0449 GMSD[ 25 ]0.2418 0.1215 0.1291 0.0259 0.2622
Table 2. Ranking of different evaluation algorithms
View tableTable 2. Ranking of different evaluation algorithms
Algorithm I07_11_5 I07_12_4 I07_15_3 I07_17_4 I07_24_5 Subjective score 4 3 2 1 5 QSR-SIM 4 3 2 1 5 VSI 4 3 2 1 5 SR-SIM 4 3 2 1 5 FSIM 4 3 2 1 5 SSIM 5 3 1 2 4 VSNR 4 1 2 3 5 PSNR 5 2 1 3 4 GMSD 4 2 3 1 5
Table 3. Comparison of time complexity of algorithms
View tableTable 3. Comparison of time complexity of algorithms
Database Time /s QSSIM QSR-SIM I17_11_2 1.1124 0.7474 TID2013 520 485
Table 4. Comparison of various color image quality assessment methods' performance
View tableTable 4. Comparison of various color image quality assessment methods' performance
Database Parameter PSNR SSIM FSIM GMSD MS-GMSD SR-SIM QSR-SIM TID2013 SROCC 0.6869 0.7417 0.8015 0.8030 0.8139 0.8073 0.8169 KROCC 0.4958 0.5588 0.6289 0.6352 0.6467 0.6404 0.6268 PLCC 0.6748 0.7895 0.8589 0.8575 0.8618 0.7970 0.8413 RMSE 0.9149 0.7608 0.6349 0.4762 0.6288 0.6193 0.6701 CSIQ SROCC 0.8058 0.8756 0.9242 0.9515 0.9545 0.9319 0.9435 KROCC 0.6084 0.6907 0.7567 0.8021 0.8075 0.7725 0.7821 PLCC 0.8000 0.8613 0.9120 0.9453 0.9512 0.9250 0.8049 RMSE 0.1575 0.1334 0.1077 0.0856 0.0810 0.0997 0.1618
Table 5. SROCC values for different distortion types for various evaluation algorithms in the TID2013 database
View tableTable 5. SROCC values for different distortion types for various evaluation algorithms in the TID2013 database
Database Distortion type MS-SSIM[ 26 ]SSIM_I[ 27 ]SSIM IFC[ 28 ]VSNR IW-SSIM FSIM SR-SIM VSI QSR-SIM TID2013 AGN 0.8646 0.8627 0.8671 0.6612 0.8271 0.8438 0.8973 0.9253 0.9460 0.9138 ANC 0.7730 0.7763 0.7726 0.5352 0.7305 0.7515 0.8208 0.8570 0.8705 0.8111 SCN 0.8544 0.8505 0.8515 0.6601 0.8013 0.8167 0.8750 0.9225 0.9367 0.8900 MN 0.8073 0.7895 0.7767 0.6932 0.7072 0.8020 0.7944 0.7860 0.7697 0.7036 HFN 0.8604 0.8688 0.8634 0.7406 0.8455 0.8553 0.8984 0.9132 0.9200 0.9042 IN 0.7629 0.7896 0.7503 0.6408 0.7363 0.7281 0.8072 0.8277 0.8741 0.7885 QN 0.8706 0.8411 0.8657 0.6282 0.8357 0.8468 0.8719 0.8502 0.8748 0.8626 GB 0.9673 0.9724 0.9668 0.8907 0.9470 0.9701 0.9551 0.9620 0.9612 0.9118 DEN 0.9268 0.9296 0.9254 0.7779 0.9081 0.9152 0.9302 0.9403 0.9484 0.9366 JPEG 0.9265 0.9227 0.9200 0.8357 0.9008 0.9187 0.9324 0.9386 0.9541 0.9219 JP2K 0.9504 0.9575 0.9468 0.9078 0.9273 0.9506 0.9577 0.9674 0.9706 0.9522 JGTE 0.8475 0.8581 0.8493 0.7425 0.7908 0.8388 0.8464 0.8543 0.9216 0.7764 J2TE 0.8889 0.8856 0.8828 0.7769 0.8407 0.8656 0.8913 0.9166 0.9228 0.8355 NEPN 0.7968 0.7885 0.7821 0.5737 0.6653 0.8011 0.7917 0.7975 0.8060 0.8141 Block 0.4801 0.4563 0.5720 0.2414 0.1771 0.3717 0.5489 0.4731 0.1713 0.5545 MS 0.7906 0.7845 0.7752 0.5522 0.4871 0.7833 0.7531 0.6576 0.7700 0.7762 CTC 0.4634 0.3800 0.3775 0.1798 0.3320 0.4593 0.4686 0.4705 0.4754 0.4671 CCS 0.4099 0.4208 0.4141 0.4029 0.3677 0.4196 0.2748 0.2053 0.8100 0.5359 MGN 0.7786 0.8092 0.7803 0.6143 0.7644 0.7728 0.8469 0.8778 0.9117 0.8110 CN 0.8528 0.8711 0.8566 0.8160 0.8683 0.8762 0.9121 0.9263 0.9243 0.9084 LCNI 0.9068 0.9173 0.9057 0.8180 0.8821 0.9037 0.9466 0.9608 0.9564 0.9406 ICQD 0.8555 0.8351 0.8542 0.6006 0.8667 0.8401 0.8760 0.8803 0.8839 0.8795 CHA 0.8784 0.8771 0.8775 0.8210 0.8645 0.8682 0.8715 0.8754 0.8906 0.8494 SSR 0.9483 0.9488 0.9461 0.8885 0.9339 0.9474 0.9565 0.9614 0.9628 0.9625
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Jing Yue, Guojun Liu, Hao Fu. Color Image Quality Assessment Based on Quaternion Spectral Residual[J]. Laser & Optoelectronics Progress, 2019, 56(3): 031009
Paper Information
Category: Image Processing
Received: Aug. 29, 2018
Accepted: Sep. 18, 2018
Published Online: Jul. 31, 2019
The Author Email: Jing Yue (yjing1995@163.com), Guojun Liu (liugj@nxu.edu.cn)
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