A Novel Gabor Filtering and Adaptive Histogram Equalization Method for Improving Images

Main Article Content

Anne Gowda A B
Nataraja N
Santosh Kumar S
Sunil Kumar K N
Satya Srikanth Palle

Abstract

The correct information may only sometimes be effectively conveyed by images due to various factors, such as excessively bright or dark lighting and low or high contrast. As a result, picture improvement has become an essential part of digital image processing. This proposed method aims to develop an algorithm for improving photos captured in dark environments. This letter presents a new picture-enhancing approach that combines median and Gabor filtering using the wavelet domain with histogram equalization working over a spatial domain. The proposed method in this paper combines spatial and transformed domains for image enhancement and has been simulated using MATLAB. The simulation results of two different photos show that the suggested approach extends the histogram over a wide range of grayscale, offering a superior improvement to the original image. The novel proposed algorithm aims to improve image quality and visibility, making identifying essential details within the image easier. Further, the proposed technique's success is manifested by examining the produced photos' contrast and brightness. The findings reveal that the suggested technique beats the other strategies for improving low-contrast photos.

Article Details

How to Cite
Gowda A B, A. ., N, N. ., Kumar S, S. ., Kumar K N, S. ., & Srikanth Palle, S. . (2023). A Novel Gabor Filtering and Adaptive Histogram Equalization Method for Improving Images. International Journal on Recent and Innovation Trends in Computing and Communication, 11(7), 194–199. https://doi.org/10.17762/ijritcc.v11i7.7845
Section
Articles

References

Sana'a khudayer Jadwaa, MRI Brain Tumor Imaging Enhancement Methods: A Review, International Journal of Computer Engineering and Information Technology 11:153, 2019.

R. Firoz, M.S. Ali, M.N.U. Khan, M.K. Hossain, M.K. Islam Md Shahinuzzaman, Medical image enhancement using morphological transformation, Journal of Data Analysis and Information Processing,4:1,2016.

Wang, Q., Li, L., Tan, C. L., & Xia, T.,Image enhancement of historical documents using directional wavelet,International Journal of Wavelets, Multiresolution and Information Processing, 1:291,2003.

J. -M. Ling, R. -Y. Lee and C. -W. Ling, Denoising and Contrast Enhancement of Medical Image using Wavelet Thresholding Approach, 2020 3rd IEEE International Conference on Knowledge Innovation and Invention (ICKII),340, 2020..

Li, X., Li, T., Zhao, H., Dou, Y., & Pang, C.,Medical image enhancement in F-shift transformation domain,Health information science and systems, 7:1, 2019.

Srinivasan, S., & Balram, N.,Adaptive contrast enhancement using local region stretching,In Proceedings of the 9th Asian symposium on information display,152, 2006.

G. Arockia Selva,Saroja P. V.,Image Enhancement Using Different Forms Of Hex-Gabor Filter: A Comparative Analysis, European Journal of Molecular & Clinical Medicine,7:1483,2020.

Podgantwar, U. D., & Raut, U. K.,Extraction of finger vein patterns using gabor filter in finger vein image profiles,International Journal of Engineering Research and Technology, 2:3294, 2013.

Zhu, E., Yin, J., & Zhang, G.,Fingerprint enhancement using circular gabor filter. In Image Analysis and Recognition, International Conference ICIAR 2004,750, 2004.

Putra, R. D., Purboyo, T. W., & Prasasti, A. L..A review of image enhancement methods, International Journal of Applied Engineering Research, 12:13596,2017.

Ackar, H., Abd Almisreb, A., & Saleh, M. A., A review on image enhancement techniques,Southeast Europe Journal of Soft Computing, 8:1,2019.

Xiong, J., Yu, D., Wang, Q., Shu, L., Cen, J., Liang, Q., & Sun, B, Application of histogram equalization for image enhancement in corrosion areas, Shock and Vibration,1, 2021.

Dar, K. A., & Mittal, S, An enhanced adaptive histogram equalization based local contrast preserving technique for HDR images, In IOP Conference Series: Materials Science and Engineering,1022:012,2021.

Yahya Ghufran Khidhir, Ameer Hussein Morad. (2023). Real-Time End-to-End Self-Driving Car Navigation. International Journal of Intelligent Systems and Applications in Engineering, 11(2s), 366–372. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2732

Mishra, A. K., & Panda, C. S., A Review Paper on Low Light Image Enhancement Methods for Un-uniform Illumination, IFAC-PapersOnLine,55:287, 2022.

Dorothy, R., Joany, R. M., Rathish, R. J., Prabha, S. S., Rajendran, S., & Joseph, S.,Image enhancement by histogram equalization, International Journal of Nano Corrosion Science and Engineering, 2:21, 2015.

S. Muniyappan, A. Allirani and S. Saraswathi, A novel approach for image enhancement by using contrast limited adaptive histogram equalization method," 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 1, 2013.

Lidong, H., Wei, Z., Jun, W., & Zebin, S, Combination of contrast limited adaptive histogram equalisation and discrete wavelet transform for image enhancement,IET Image Processing, 9:908, 2015.

Ekaterina Katya, S.R. Rahman. (2020). Void Node Detection and Packet Re-routing in Underwater Wireless Sensor Network. International Journal of New Practices in Management and Engineering, 9(04), 01 - 10. Retrieved from http://ijnpme.org/index.php/IJNPME/article/view/93

Rajput, S., & Suralkar, S. R., Comparative study of image enhancement techniques,International Journal of Computer Science and Mobile Computing, 2:11, 2013.

N. Sharma, S. Saurav, S. Singh, R. Saini and A. K. Saini,A comparative analysis of various image enhancement techniques for facial images,2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2279, 2015.

Paul Garcia, Ian Martin, Laura López, Sigurðsson Ólafur, Matti Virtanen. Deep Learning Models for Intelligent Tutoring Systems. Kuwait Journal of Machine Learning, 2(1). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/167

Jeevan K. M, et al., Wavelet thresholding based denoising technique for a color image, ARPN Journal of Engineering and Applied Sciences,15:3034, 2020.

Hashmi, A., Juneja, A., Kumar, N., Gupta, D., Turabieh, H., Dhingra, G., Bitsue, Z. K., Contrast Enhancement in Mammograms Using Convolution Neural Networks for Edge Computing Systems,Scientific Programming, 2022.

Narayanaswamy Anughna, and Muniyappa Ramesha , Antenna Reconfiguration Based DOA Estimation for AWGN Channel in MIMO applications, Progress In Electromagnetics Research,128:73,2023.

N. Anughna and M. Ramesha, Performance Analysis on various Diversity Schemes with Channel Equalization and Estimation Techniques in MIMO OFDM system,3rd International Conference for Emerging Technology (INCET), 1,2022.

Carmen Rodriguez, Predictive Analytics for Disease Outbreak Prediction and Prevention , Machine Learning Applications Conference Proceedings, Vol 3 2023.

A. N and R. M, “Performance Analysis on 5G Waveform Candidates for MIMO Technologies,” 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon),1,2022.