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Efficient retrieval algorithm for multimedia image information

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Abstract

The research on the retrieval of multimedia image data information is of great significance for increasing the retrieval rate of multimedia image information. Due to the certain similar characteristics of massive multimedia image information, the picture information features are confused. The traditional image retrieval method mainly uses the image information feature to classify and retrieve. When the picture information is disordered, it is impossible to classify the mass multimedia image information features, resulting in slow retrieval speed and low accuracy. A new high-efficiency retrieval algorithm for massive multimedia image information is proposed and optimized. Based on the theory of granular computing, an image region similarity measurement method for content retrieval is proposed. The image feature information table is transformed into an ordered matrix form. By studying the ordered matrix, the concept of image feature granules and granule granules is introduced, the importance of image features is analyzed from different granularity levels, and the order relationship between regions in the image feature information table is maintained, and the weight of the theoretical image feature is calculated based on the granularity for implementing the image region similarity measurement method. The example shows that the similarity measure method can measure the degree of similarity between image regions objectively and effectively, and provides a new idea and method for the research of granular computing theory in multimedia image content retrieval.

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References

  1. Ahn SH, Lee KT, Rim SH et al (2018) Surface downward longwave radiation retrieval algorithm for GEO-KOMPSAT-2A/AMI[J]. Asia-Pac J Atmos Sci 54(2):237–251

    Article  Google Scholar 

  2. Azadeh A, Goodarzi AH, Kolaee MH et al (2018) An efficient simulation–neural network–genetic algorithm for flexible flow shops with sequence-dependent setup times, job deterioration and learning effects[J]. Neural Comput & Applic 2018(3):1–15

    Google Scholar 

  3. Bach H, Klug P, Ruf T et al (2015) Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity[J]. ISPRS – Int Arch Photogramm Remote Sens Spat Inf Sci XL-7/W3(7):1–7

    Google Scholar 

  4. Baker NR, Nance RE (2014) The use of simulation in studying information storage and retrieval systems[J]. J Am Soc Inf Sci Technol 19(4):363–370

    Article  Google Scholar 

  5. Gao H, Chu D, Duan Y (2017) The probabilistic model checking based service selection method for business process modeling. Int J Softw Eng Knowl Eng 27(6):897–923

    Article  Google Scholar 

  6. Han J, Mckenna SJ (2014) Query-dependent metric learning for adaptive, content-based image browsing and retrieval[J]. IET Image Process 8(10):610–618

    Article  Google Scholar 

  7. Hong SY, Lee SJ (2015) An intelligent web digital image metadata service platform for social curation commerce environment[J]. Model Simulat Eng 2015:1–10

    Article  Google Scholar 

  8. Lee YH, Kim Y (2015) Efficient image retrieval using advanced SURF and DCD on mobile platform[J]. Multimed Tools Appl 74(7):1–11

    Article  Google Scholar 

  9. Lee YH, Rhee SB (2015) Efficient photo image retrieval system based on combination of smart sensing and visual descriptor[J]. Intell Autom Soft Co 21(1):39–50

    Article  Google Scholar 

  10. Lei CD, Zheng LH, Ying C (2015) Simulation and retrieval of stitching tolerances of aspheric sector-shaped segment[J]. Acta Photonica Sin 44(6):101–106

    Google Scholar 

  11. Li G, Zhu L, Katsaggelos A (2013) An efficient video indexing and retrieval algorithm using the luminance field trajectory modeling[J]. IEEE Transactions on Circuits & Systems for Video Technology 19(10):1566–1570

    Google Scholar 

  12. Li HS, Zhu Q, Zhou RG et al (2014) Multidimensional color image storage, retrieval, and compression based on quantum amplitudes and phases[J]. Inf Sci 273(3):212–232

    Article  Google Scholar 

  13. Montomoli F, Macelloni G, Brogioni M et al (2016) Observations and simulation of multifrequency SAR data over a snow-covered boreal Forest[J]. IEEE J-STARS 9(3):1216–1228

    Google Scholar 

  14. Ouellette JD, Johnson JT, Kim S et al (2014) A simulation study of compact polarimetry for radar retrieval of soil moisture[J]. IEEE Trans Geosci Remote Sens 52(9):5966–5973

    Article  Google Scholar 

  15. Qian P, Zhou J, Jiang Y, Liang F, Zhao K, Wang S, Su K-H, Muzic RF Jr (2018) Multi-view maximum entropy clustering by jointly leveraging inter-view collaborations and intra-view-weighted attributes. IEEE Access 6:28594–28610

    Article  Google Scholar 

  16. Sanders AFJ, De Haan JF, Sneep M et al (2015) Evaluation of the operational aerosol layer height retrieval algorithm for Sentinel-5 precursor: application to O2 a band observations from GOME-2A[J]. Atmos Meas Tech 8(11):4947–4977. 8(6):6045-6118

    Article  Google Scholar 

  17. Shao Y, Liu Y, Li C (2015) Intermediate model based efficient and integrated multidisciplinary simulation data visualization for simulation information reuse[J]. Adv Eng Softw 90(C):138–151

    Article  Google Scholar 

  18. Shechtman Y, Beck A, Eldar YC (2014) GESPAR: efficient phase retrieval of sparse signals[J]. IEEE Trans Signal Process 62(4):928–938

    Article  MathSciNet  MATH  Google Scholar 

  19. Silva SFD, Avalhais LP, Batista MA et al (2014) Findings on ranking evaluation functions for feature weighting in image retrieval[J]. J Braz Comput Soc 20(1):1–10

    Article  MathSciNet  Google Scholar 

  20. Thilagavathi S, Geetha BG (2015) Energy aware swarm optimization with intercluster search for wireless sensor network.[J]. Sci World J 2015:1–8

    Article  Google Scholar 

  21. Wang YQ, Shi JC, Liu ZH et al (2013) Retrieval algorithm for microwave surface emissivities based on multi-source, remote-sensing data: an assessment on the Qinghai-Tibet plateau[J]. Sci China Earth Sci 56(1):93–101

    Article  Google Scholar 

  22. Wang F, Wang Z, Rui L et al (2015) An efficient algorithm for harmonic retrieval by combining blind source separation with wavelet packet decomposition[J]. Digit Signal Process 46(C):133–150

    Article  MathSciNet  Google Scholar 

  23. Xia K, Liu Z (2018) Renal segmentation algorithm combined low-level features with deep coding feature[C]. In: 27th IEEE international conference on robot and human interactive communication. RO-MAN

  24. Xia L, Mao K, Ma Y et al (2014) An algorithm for retrieving land surface temperatures using VIIRS data in combination with multi-sensors[J]. Sensors 14(11):21385

    Article  Google Scholar 

  25. Xia K-J, Yin H-S, Rong G-S, Wang J-Q, Jin Y (2018) X-ray image enhancement base on the improved adaptive low-pass filtering. J Med Imag Health In 8(7):1342–1348. https://doi.org/10.1166/jmihi.2018.2472(SCI)

  26. Yue L, Guan Z, He C et al (2017) Slotting optimization of automated storage and retrieval system (AS/RS) for efficient delivery of parts in an assembly shop using genetic algorithm: a case study[J]. IOP Conf Ser: Mater Sci Eng 215(1):012–025

    Google Scholar 

  27. Zhao T, Ran Q, Lin Y et al (2015) Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography[J]. Opt Lasers Eng 72:12–17

    Article  Google Scholar 

  28. Zheng D, Velde RVD, Wen J et al (2018) Assessment of the SMAP soil emission model and soil moisture retrieval algorithms for a Tibetan Desert ecosystem[J]. IEEE Trans Geosci Remote Sens 2(99):1–14

    Article  Google Scholar 

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Correspondence to Ruobei Tong.

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Tong, L., Tong, R. & Chen, L. Efficient retrieval algorithm for multimedia image information. Multimed Tools Appl 79, 9469–9487 (2020). https://doi.org/10.1007/s11042-019-07886-6

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  • DOI: https://doi.org/10.1007/s11042-019-07886-6

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