Skip to main content
SpringerLink
Log in

Enhancement of hyperspectral remote sensing images based on improved fuzzy contrast in nonsubsampled shearlet transform domain

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

In order to deal with the pseudo-Gibbs phenomenon in the process of hyperspectral remote sensing image enhancement, a novel image enhancement method based on nonsubsampled shearlet transform (NSST) is proposed in this paper. The main motivation of this study is to adjust the coefficient of remote sensing image enhancement as a pattern recognition task. Firstly, the input image is decomposed into a low-frequency component and some high-frequency components by NSST decomposition; Secondly, the guided filter is applied to process the low-frequency component to improve the contrast, and the improved fuzzy contrast is used to suppress the noise of the high-frequency components; Thirdly, the processed coefficients of low-frequency and high-frequency are reconstructed by inverse nonsubsampled shearlet transform (INSST), and the final enhanced image is obtained. The experimental results demonstrate that the proposed approach has obvious advantages in terms of objective data and subjective vision.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Abazari R, Lakestani M (2018) A hybrid denoising algorithm based on shearlet transform method and Yaroslavsky’s filter. Multimed Tools Appl 77(14):17829–17851

    Article  Google Scholar 

  2. Ancuti CO, Ancuti C, De CV (2018) Color balance and fusion for underwater image enhancement. IEEE Trans Image Process 27(1):379–393

    Article  MathSciNet  MATH  Google Scholar 

  3. Chavan SS, Mahajan A, Talbar SN (2017) Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis. Comput Biol Med 81:64–78

    Article  Google Scholar 

  4. Da CA, Zhou J, Do MN (2006) The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans Image Process 15(10):3089–3101

    Article  Google Scholar 

  5. He K, Sun J, Tang X (2013) Guided image filtering. IEEE Trans Pattern Anal Mach Intell 35(6):1397–1409

    Article  Google Scholar 

  6. Huang Z, Ding M, Zhang X (2017) Medical image fusion based on non-subsampled shearlet transform and spiking cortical model. J Med Imaging Health Inf 7(1):229–234

    Article  Google Scholar 

  7. Jafari S, Ghofrani S (2016) Using two coefficients modeling of nonsubsampled shearlet transform for despeckling. J Appl Remote Sens 10(1):015002

    Article  Google Scholar 

  8. Ji X, Zhang G (2017) Contourlet domain SAR image de-speckling via self-snake diffusion and sparse representation. Multimed Tools Appl 76(4):5873–5887

    Article  MathSciNet  Google Scholar 

  9. Joseph J, Periyasamy R (2018) A fully customized enhancement scheme for controlling brightness error and contrast in magnetic resonance images. Biomed Signal Processing Control 39:271–283

    Article  Google Scholar 

  10. Kallel F, Sahnoun M (2018) CT scan contrast enhancement using singular value decomposition and adaptive gamma correction. SIViP 12(5):905–913

    Article  Google Scholar 

  11. Li L, Si Y (2018) Enhancement of medical images based on guided filter in nonsubsampled shearlet transform domain. J Med Imaging Health Inf 8(6):1207–1216

    Article  Google Scholar 

  12. Li Q, Jia Z, Qin X (2014) A novel remote sensing image enhancement method based on NSCT. Inf Technol J 13(1):153–158

    Article  Google Scholar 

  13. Li L, Jia Z, Yang J (2016) Noisy remote sensing image segmentation with wavelet shrinkage and graph cuts. J Indian Soc Remote Sens 44(6):995–1002

    Article  Google Scholar 

  14. Li L, Si Y, Jia Z (2017) Remote sensing image enhancement based on non-local means filter in NSCT domain. Algorithms 10(4):116

    Article  MathSciNet  MATH  Google Scholar 

  15. Li L, Si Y, Jia Z (2017) Remote sensing image enhancement based on adaptive thresholding in NSCT domain. Proceedings of 2nd International Conference on Image, Vision and Computing (ICIVC-2017) pp.319–322

  16. Li L, Si Y, Jia Z (2018) A novel brain image enhancement method based on nonsubsampled contourlet transform. Int J Imaging Syst Technol 28(2):124–131

    Article  Google Scholar 

  17. Li L, Si Y, Jia Z (2018) Medical image enhancement based on CLAHE and unsharp masking in NSCT domain. J Med Imaging Health Inf 8(3):431–438

    Article  Google Scholar 

  18. Li L, Si Y, Jia Z (2018) Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain. AIP Adv 8(3):035002

    Article  Google Scholar 

  19. Liu Y, Nie L, Han L (2015) Action2Activity: recognizing complex activities from sensor data. Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI-2015) pp. 1617–1623

  20. Liu L, Jia Z, Yang J (2015) A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking. Int J Imaging Syst Technol 25(3):199–205

    Article  Google Scholar 

  21. Liu Y, Nie L, Liu L (2016) From action to activity: sensor-based activity recognition. Neurocomputing 181:108–115

    Article  Google Scholar 

  22. Liu Y, Zhang L, Nie L (2016) Fortune teller: Predicting your career path. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-2016) pp. 201–207

  23. Liu J, Zhou C, Chen P (2017) An efficient contrast enhancement method for remote sensing images. IEEE Geosci Remote Sens Lett 14(10):1715–1719

    Article  Google Scholar 

  24. Liu L, Jia Z, Yang J (2017) A remote sensing image enhancement method using mean filter and unsharp masking in non-subsampled contourlet transform domain. Trans Inst Meas Control 39(2):183–193

    Article  Google Scholar 

  25. Liu Z, Feng Y, Chen H (2017) A fusion algorithm for infrared and visible based on guided filtering and phase congruency in NSST domain. Opt Lasers Eng 97:71–77

    Article  Google Scholar 

  26. Luo X, Zhang Z, Zhang B (2017) Image fusion with contextual statistical similarity and nonsubsampled shearlet transform. IEEE Sensors J 17(6):1760–1771

    Article  Google Scholar 

  27. Lv D, Jia Z, Yang J (2016) Remote sensing image enhancement based on the combination of nonsubsampled shearlet transform and guided filtering. Opt Eng 55(10):103104

    Article  Google Scholar 

  28. Math SSP, Kaliyaperumal V (2017) Enhancement of SAR images using fuzzy shrinkage technique in curvelet domain. Sādhanā 42(9):1505–1512

    Article  MATH  Google Scholar 

  29. Pu X, Jia Z, Wang L (2014) The remote sensing image enhancement based on nonsubsampled contourlet transform and unsharp masking. Concurr Comput Pract Experience 26(3):742–747

    Article  Google Scholar 

  30. Quevedo E, Delory E, Callico GM (2017) Underwater video enhancement using multi-camera super-resolution. Opt Commun 404:94–102

    Article  Google Scholar 

  31. Ren R, Gu L, Fu H (2017) Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery. J Appl Remote Sens 11:026014

    Article  Google Scholar 

  32. Sharif M, Hussain A, Jaffar MA (2015) Fuzzy similarity based non local means filter for Rician noise removal. Multimed Tools Appl 74(15):5533–5556

    Article  Google Scholar 

  33. Singh P, Raman B, Misra M (2018) Just process me, without knowing me: a secure encrypted domain processing based on Shamir secret sharing and POB number system. Multimed Tools Appl 77(10):12581–12605

    Article  Google Scholar 

  34. Tao F, Wu Y (2015) Remote sensing image enhancement based on non-subsampled shearlet transform and parameterized logarithmic image processing model. Acta Geodaet Et Cartographica Sin 44(8):884–892

    Google Scholar 

  35. Wang Y, Pan Z (2017) Image contrast enhancement using adjacent-blocks-based modification for local histogram equalization. Infrared Phys Technol 86:59–65

    Article  Google Scholar 

  36. Wang C, Ye Z (2005) Brightness preserving histogram equalization with maximum entropy: a variational perspective. IEEE Trans Consum Electron 51(4):1326–1334

    Article  Google Scholar 

  37. Wang J, Jia Z, Qin X (2015) Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast. Int J Imaging Syst Technol 25(1):7–14

    Article  Google Scholar 

  38. Wang X, Liu Y, Zhang N (2015) An edge-preserving adaptive image denoising. Multimed Tools Appl 74(24):11703–11720

    Article  Google Scholar 

  39. Wu Y, Shi J (2015) Image enhancement in non-subsampled contourlet transform domain based on multi-scale retinex. Acta Opt Sin 35(3):79–88

    Google Scholar 

  40. Wu Y, Meng T, Wu S (2015) Adaptive image enhancement based on NSST and constraint of human eye perception information fidelity. J Optoelectron Laser 26(5):978–985

    Google Scholar 

  41. Wu C, Liu Z, Jiang H (2017) Choosing the filter for catenary image enhancement method based on the non-subsampled contourlet transform. Rev Sci Instrum 88(5):054701

    Article  Google Scholar 

  42. Yang B, Jia Z, Qin X (2013) Remote sensing image enhancement based on shearlet transform. J Optoelectron Laser 24(11):2249–2253

    Google Scholar 

  43. Zhan K, Shi J, Teng J (2017) Linking synaptic computation for image enhancement. Neurocomputing 238:1–12

    Article  Google Scholar 

  44. Zhang Q, Maldague X (2017) Multisensor image fusion approach utilizing hybrid pre-enhancement and double nonsubsampled contourlet transform. J Electron Imaging 26(1):010501

    Article  Google Scholar 

  45. Zhang J, Geng W, Liang X (2017) Hyperspectral remote sensing image retrieval system using spectral and texture features. Appl Opt 56(16):4785–4796

    Article  Google Scholar 

  46. Zhang Q, Shen S, Su X (2017) A novel method of medical image enhancement based on wavelet decomposition. Autom Control Comput Sci 51(4):263–269

    Article  Google Scholar 

  47. Zhou S, Zhang F, Siddique MA (2015) Range limited peak-separate fuzzy histogram equalization for image contrast enhancement. Multimed Tools Appl 74(17):6827–6847

    Article  Google Scholar 

Download references

Acknowledgments

We thank all the volunteers and colleagues provided helpful comments on previous versions of the manuscript. The experimental measurements and data collection were carried out by Liangliang Li and Yujuan Si. The manuscript was written by Liangliang Li with assistance of Yujuan Si. We would like to thank Prof. Yujuan Si for her contributions in proofreading of the paper. This work was supported by the Key Scientific and Technological Research Project of Jilin Province under Grant Nos. 20150204039GX and 20170414017GH; the Natural Science Foundation of Guangdong Province under Grant No. 2016A030313658; the Innovation and Strengthening School Project (provincial key platform and major scientific research project) supported by Guangdong Government under Grant No. 2015KTSCX175; the Premier-Discipline Enhancement Scheme Supported by Zhuhai Government under Grant No. 2015YXXK02-2; the Premier Key-Discipline Enhancement Scheme Supported by Guangdong Government Funds under Grant No. 2016GDYSZDXK036.

Author information

Authors and Affiliations

  1. College of Communication Engineering, Jilin University, Changchun, 130012, China

    Liangliang Li & Yujuan Si

  2. Department of Electronic Information, Zhuhai College of Jilin University, Zhuhai, 519041, China

    Yujuan Si

Authors
  1. Liangliang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yujuan Si
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yujuan Si.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, L., Si, Y. Enhancement of hyperspectral remote sensing images based on improved fuzzy contrast in nonsubsampled shearlet transform domain. Multimed Tools Appl 78, 18077–18094 (2019). https://doi.org/10.1007/s11042-019-7203-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-7203-6

Keywords

Search

Navigation