Two general filters for image enhancement and their applications for images acquired from a transmission electron microscope and a fluorescence microscope
DOI: 10.23977/acss.2026.100102 | Downloads: 2 | Views: 55
Author(s)
Jiangqi Luo 1, Ling Zhang 2, Yingcheng Lin 2, Ye Wu 3,4
Affiliation(s)
1 Qigongxi Industrial Design Center, Qinhuai District, Nanjing, 211000, China
2 College of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China
3 School of Electrical and Information Engineering, Hunan Institute of Technology, Hengyang, 421002, China
4 School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, 210046, China
Corresponding Author
Ling ZhangABSTRACT
Image enhancement is important in image processing. It can improve image contrast, highlight details and suppress noise. This work proposes two general filters based on mathematical functions for the image enhancement. The first filter was designed using logarithmic, anti-trigonometric and hypotenuse functions. The second filter was designed using trigonometric and anti-trigonometric functions. These two filters can be used for processing the images acquired from fluorescence microscope and transmission electron microscope. We also use them to process images containing nesting structures, weak-light images and images with high degradation by the Gaussian noise. They are effective to achieve better enhancement of the images.
KEYWORDS
Image enhancement; matched filters; low-light images; transmission electron microscope; fluorescence microscope; near infrared imagingCITE THIS PAPER
Jiangqi Luo, Ling Zhang, Yingcheng Lin, Ye Wu. Two general filters for image enhancement and their applications for images acquired from a transmission electron microscope and a fluorescence microscope. Advances in Computer, Signals and Systems (2026) Vol. 10: 10-17. DOI: http://dx.doi.org/10.23977/acss.2026.100102.
REFERENCES
[1] Qi,Y.,Yang,Z., Sun,W., Lou, M., Lian,J., Zhao,W., Deng,X. and Ma,Y. (2021) A Comprehensive Overview of Image Enhancement Techniques. Arch. Comp. Met. Eng. 29,583-607.
[2] Lin, S.C.F., Wong, C.Y., Rahman, M.A., Jiang, G., Liu, S., Kwok, N., Shi, H., Yu, Y.-H. and Wu, T. (2015) Image enhancement using the averaging histogram equalization (AVHEQ) approach for contrast improvement and brightness preservation. Com. & Elec. Eng. 46,356-370.
[3] Cho, D. and Bui, T.D. (2014) Fast image enhancement in compressed wavelet domain. Signal Process., 98,295-307.
[4] Liu, T., Zhang, W.and Yan, S.(2015) A novel image enhancement algorithm based on stationary wavelet transform for infrared thermography to the de-bonding defect in solid rocket motors. Mecha. Sys. Sign. Proce. 62-63,366-380.
[5] Khatkar, K. and Kuman, D. (2015) Biomedical Image Enhancement Using Wavelets. Procedia Comp. Sci. 48, 513-517.
[6] Wang, Y., Wang, H.,Yin, C. and Dai, M. (2016) Biologically inspired image enhancement based on Retinex. Neurocomputing, 177,373-384.
[7] Tang, L., Chen, S., Liu, W.and Li, Y. (2011) Improved Retinex Image Enhancement Algorithm. Procedia Environ. Sci. 11,208-212.
[8] Zotin, A. (2018) Fast Algorithm of Image Enhancement based on Multi-Scale Retinex. Procedia Comp. Sci. 131, 6-14.
[9] Jiang, X., Yao, H. and Liu, D. (2018) Nighttime image enhancement based on image decomposition.Sign. Image Video Process.13,189-197.
[10] Cheng, H.D. and Xu, H. (2000) A novel fuzzy logic approach to contrast enhancement. Pattern Recognition. 33, 809-819.
[11] Yu,C.-Y., Lin,H.-Y. and Lin, C.-J.(2021) Image contrast expand enhancement system based on fuzzy theory. Microsystem Tech. 27,1579-1587.
[12] Li,C., Yang,Y., Xiao,L., Li,Y., Zhou,Y. and Zhao,J.(2016) A novel image enhancement method using fuzzy Sure entropy. Neurocomputing.215,196-211.
[13] Selvam, C. and Sundaram, D.(2025) Interval-valued intuitionistic fuzzy generator based low-light enhancement model for referenced image datasets. Artificial Intelligence Review. 58,141.
[14] Jiang, Y., Tong, G., Yin, H. and Xiong, N.(2019) A Pedestrian Detection Method Based on Genetic Algorithm for Optimize XGBoost Training Parameters. IEEE Access. 7, 118310-118321.
[15] Lu, Y., Wu, S., Fang, Z., Xiong, N., Yoon, S. and Park, D. S.(2017) Exploring finger vein based personal authentication for secure IoT.Future Generation Computer Systems. 77, 149-160.
[16] Wan, R., Xiong, N. and The Loc, N. (2018) An energy-efficient sleep scheduling mechanism with similarity measure for wireless sensor networks. Hum. Cent. Comput. Inf. Sci. 8, 1-22.
[17] Xia, F., Hao, R., Li, J.,Xiong, N., Yang, L. T. and Zhang, Y.(2013) Adaptive GTS allocation in IEEE 802.15.4 for real-time wireless sensor networks. J. Sys. Architect. 59, 1231-1242.
[18] Yao, Y., Xiong, N., Park. J. H., Ma, L. and Liu, J.(2013) Privacy-preserving max/min query in two-tiered wireless sensor networks. Computers & Mathematics with Applications. 65, 1318-1325.
[19] Sobbahi, R. and Tekli, J.(2022) Signal Proce. Comparing deep learning models for low-light natural scene image enhancement and their impact on object detection and classification: Overview, empirical evaluation, and challenges. Image Comm. 109,116848.
[20] Sobbahi,R. and Tekli, J.(2022) Low-Light Homomorphic Filtering Network for integrating image enhancement and classification. Sig. Proce. - Image Comm. 100,116527.
[21] Sun, T., Xu,J., Li, Z. and Wu, Y. (2025) Two Non-Learning Systems for Profile-Extraction in Images Acquired from a near Infrared Camera, Underwater Environment, and Low-Light Condition. Applied Sciences. 15,11289.
[22] Zhou, B., Wang, W., Wang, J., Gu, H. and Wu,Y. (2025) Application of Frequency Domain Filter Banks in Audio Denoising. 2025 8th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE).360-364.
[23] Jia,M., Xu, J., Yang, R., Li, Z., Zhang, L. and Wu, Y.(2023) Three filters for the enhancement of the images acquired from fluorescence microscope and weak-light-sources and the image compression. Heliyon. 9,e20191.
[24] Lin, Y., Zhang,L., Xu, J. and Wu, Y. (2025) Three Filters for Enhancing Images Acquired from Blue Fluorescence Imaging, Low Light Condition, and a Near Infrared Camera. International Journal of Epidemiology and Public Health Research. 7(1).
[25] Huang, Y., Yang, R., Geng, X., Li, Z. and Wu, Y.(2023) Two Filters for Acquiring the Profiles from Images Obtained from Weak-Light Background, Fluorescence Microscope, Transmission Electron Microscope, and Near-Infrared Camera. Sensors.23,6207.
[26] Yang, R., Chen, L., Zhang, L., Li,Z.,Lin,Y. and Wu, Y. (2023) Image enhancement via special functions and its application for near infrared imaging. Global Challenges. 7, 2200179.
[27] Wu, J. and Wu,Y. (2025) Two Filters Based on Simple Functions for Extracting Profiles from Images. Advances in Computer, Signals and Systems.9,3.
[28] Li, Z., Yao, S., Xu, J., Wu, Y., Li, C. and He, Z. (2018) Endoscopic near‐infrared dental imaging with indocyanine green: a pilot study. Annals of the New York Academy of Sciences. 1421,88-96.
[29] Zhu, J., Shao, X.J., Li, Z., Lin, C.H., Wang, C.W.Q., Jiao, K., Xu, J., Pan, H.X. and Wu, Y. (2022) Synthesis of holmium-oxide nanoparticles for near-infrared imaging and dye-photodegradation. Molecules. 27, 3522.
[30] Li, Z., Li, Y., Lin, Y., Alam, M.Z. and Wu, Y. (2020) Synthesizing Ag+: MgS, Ag+: Nb2S5, Sm3+: Y2S3, Sm3+:Er2S3, and Sm3+:ZrS2 Compound Nanoparticles for Multicolor Fluorescence Imaging of Biotissues.ACS Omega. 5,32868-32876.
[31] Wu, Y., Ou, P., Song, J., Zhang, L., Lin, Y., Song, P. and Xu, J. (2020) Synthesis of praseodymium-and molybdenum-sulfide nanoparticles for dye-photodegradation and near-infrared deep-tissue imaging. Materials Research Express. 7,036203.
[32] Fu, H., Ou, P., Zhu, J., Song, P., Yang, J and Wu, Y.(2019) Enhanced protein adsorption in fibrous substrates treated with zeolitic imidazolate framework-8 (ZIF-8) nanoparticles. ACS Applied Nano Materials. 2, 7626-7636.
[33] Wu,Y., Ou, P., Fronczek, F.R.,Song,J., Lin,Y., Wen,H.M. and Xu, J.(2019) Simultaneous Enhancement of Near-Infrared Emission and Dye Photodegradation in a Racemic Aspartic Acid Compound via Metal-Ion Modification.ACS Omega. 4, 19136-19144.
[34] Wu, Y., Yang,J., Lin,Y., Xu, J.(2019) Synthesis of samarium-based metal organic compound nanoparticles with polychromatic-photoluminescence for bio-tissue fluorescence imaging. Molecules.24,3657.
[35] Wu,Y., Xu, J., Guo,R. (2019) Achieving near-infrared deep tissue imaging via metal organic complex nanoparticles. Photonic Fiber and Crystal Devices: Advances in Materials and Innovations in Device Applications XIII. 11123,143-149.
[36] Wu, Y., Lin,Y., Xu,J.(2019) Synthesis of Ag–Ho, Ag–Sm, Ag–Zn, Ag–Cu, Ag–Cs, Ag–Zr, Ag–Er, Ag–Y and Ag–Co metal organic nanoparticles for UV-Vis-NIR wide-range bio-tissue imaging. Photochemical &Photobiological Sciences.18,1081-1091.
[37] Li, F., Yang, R., Xu, J., Xu, G., Wu, Y. (2024) Detecting N-Phenyl-2-Naphthylamine, L-Arabinose, D-Mannose, L-Phenylalanine, L-Methionine, and D-Trehalose via Photocurrent Measurement.Gels.10,808.
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