An optimal adaptive thresholding based sub-histogram equalization for brightness preserving image contrast enhancement. (English) Zbl 1450.94006
Summary: In this paper, a new adaptive thresholding based sub-histogram equalization (ATSHE) scheme is proposed for contrast enhancement and brightness preservation with retention of basic image features. The histogram of an input image is divided into different sub-histogram using adaptive thresholding intensity values. The number of threshold values or sub-histograms of the image are not fixed, but depends on the peak signal-to-noise ratio (PSNR) of the thresholded image. Histogram clipping is also used here to control the undesired enhancement of resultant image thus avoiding over-enhancement. Median value of the original histogram gives the threshold value of clipping process. The main objective of proposed method is to improve contrast enhancement with preservation of mean brightness value, structural similarity index (SSIM) and information content of the images. Image contrast enhancement is examined by well-known enhancement assessment parameters such as contrast per pixel and modified measure of enhancement. The mean brightness preservation of the image is evaluated by using absolute mean brightness error value and feature preservation qualities are checked through SSIM and PSNR values. Through the proposed routine, the enhanced images achieve a good trade-off between features enhancement, low contrast boosting and brightness preservation in addition with the natural feel of the original image. In particular, the proposed ATSHE scheme due to its adaptive nature of threshold selection can successfully enhance images under oodles of weak illumination situations such as backlighting effects, non-uniform illumination low contrast and dark images.
MSC:
| 94A08 | Image processing (compression, reconstruction, etc.) in information and communication theory |
Keywords:
adaptive thresholding; brightness preservation; contrast enhancement; peak signal-to-noise ratio; sub-histogram equalization; color satellite imagesReferences:
| [1] | Abdullah-Al-Wadud, M. (2007). A dynamic histogram equalization for image contrast enhancement. IEEE Transactions on Consumer Electronics,53, 593-600. · doi:10.1109/TCE.2007.381734 |
| [2] | Agaian, S. S., Silver, B., & Panetta, K. A. (2007). Transform coefficient histogram-based image enhancement algorithms using contrast entropy. IEEE Transactions on Image Processing,16(3), 741-758. · doi:10.1109/TIP.2006.888338 |
| [3] | Arora, S., Acharya, J., Verma, A., & Panigrahi, P. K. (2008). Multilevel thresholding for image segmentation through a fast statistical recursive algorithm. Pattern Recognition Letters,29(2), 119-125. · doi:10.1016/j.patrec.2007.09.005 |
| [4] | Bhandari, A. K., Kumar, A., Chaudhary, S., & Singh, G. K. (2017). A new beta differential evolution algorithm for edge preserved colored satellite image enhancement. Multidimensional Systems and Signal Processing,28(2), 495-527. · Zbl 1386.94006 · doi:10.1007/s11045-015-0353-4 |
| [5] | Bhandari, A. K., Kumar, A., & Padhy, P. K. (2011). Enhancement of low contrast satellite images using discrete cosine transform and singular value decomposition. World Academy of Science, Engineering and Technology,55, 35-41. |
| [6] | Bhandari, A. K., Kumar, A., Singh, G. K., & Soni, V. (2016). Dark Satellite image enhancement using knee transfer function and gamma correction based on DWT-SVD. Multidimensional System and Signal Process.,27(2), 453-476. · doi:10.1007/s11045-014-0310-7 |
| [7] | Bhandari, A. K., Maurya, S., & Meena, A. K. (2018). Social spider optimization based optimally weighted Otsu thresholding for image enhancement. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2018.2870157. · doi:10.1109/JSTARS.2018.2870157 |
| [8] | Bhandari, A. K., Singh, V. K., Kumar, A., & Singh, G. K. (2014a). Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy. Expert Systems with Applications,41(7), 3538-3560. · doi:10.1016/j.eswa.2013.10.059 |
| [9] | Bhandari, A. K., Soni, V., Kumar, A., & Singh, G. K. (2014b). Cuckoo search algorithm based satellite image contrast image and brightness enhancement using DWT-SVD. ISA Transactions,53(4), 1286-1296. · doi:10.1016/j.isatra.2014.04.007 |
| [10] | Celik, T., & Tjahjadi, T. (2010). Unsupervised colour image segmentation using dual-tree complex wavelet transform. Computer Vision and Image Understanding,114(7), 813-826. · doi:10.1016/j.cviu.2010.03.002 |
| [11] | Chen, S.-D., & Ramli, A. R. (2003a). Minimum mean brightness error bi-histogram equalization in contrast enhancement. IEEE Transactions on Consumer Electronics,49(4), 1310-1319. · doi:10.1109/TCE.2003.1261234 |
| [12] | Chen, S.-D., & Ramli, A. R. (2003b). Contrast enhancement using recursive-mean-separate histogram equalization for scalable brightness preservation. IEEE Transactions on Consumer Electronics,49(4), 1301-1309. · doi:10.1109/TCE.2003.1261233 |
| [13] | Cheng, H.-D., & Xu, H. (2000). A novel fuzzy logic approach to contrast enhancement. Pattern Recognition,33(5), 809-819. · doi:10.1016/S0031-3203(99)00096-5 |
| [14] | Demirel, H., Ozcinar, C., & Anbarjafari, G. (2010). Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition. IEEE Geoscience and Remote Sensing Letters,7(2), 333-337. · doi:10.1109/LGRS.2009.2034873 |
| [15] | Fu, X., Liao, Y., Zeng, D., Huang, Y., Zhang, X.-P., & Ding, X. (2015). A probabilistic method for image enhancement with simultaneous illumination and reflectance estimation. IEEE Transactions on Image Processing,24(12), 4965-4977. · Zbl 1408.94190 · doi:10.1109/TIP.2015.2474701 |
| [16] | Fu, X., Zeng, D., Huang, Y., Liao, Y., Ding, X., & Paisley, J. (2016). A fusion-based enhancing method for weakly illuminated images. Signal Processing,129, 82-96. · doi:10.1016/j.sigpro.2016.05.031 |
| [17] | Gonzalez, R. C., & Woods, R. E. (2011). Digital image processing (3rd ed.). Upper Saddle River: Pearson Prentice Hall. |
| [18] | Hasikin, K., & Isa, N. A. M. (2014). Adaptive fuzzy contrast factor enhancement technique for low contrast and nonuniform illumination images. Signal, Image and Video Processing,8(8), 1591-1603. · doi:10.1007/s11760-012-0398-x |
| [19] | He, K., Sun, J., & Tang, X. (2011). Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence,33(12), 2341-2353. · doi:10.1109/TPAMI.2010.168 |
| [20] | Huang, S.-C., & Yeh, C.-H. (2013). Image contrast enhancement for preserving mean brightness without losing image features. Engineering Applications of Artificial Intelligence,26(5), 1487-1492. · doi:10.1016/j.engappai.2012.11.011 |
| [21] | Kim, Y. T. (1997). Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Transactions on Consumer Electronics,43, 1-8. · doi:10.1109/30.580378 |
| [22] | Kong, N. S. P., Ibrahim, H., Ooi, C. H., Chieh, D. C. J. (2009). Enhancement of microscopic images using modified self-adaptive plateau histogram equalization. In International conference on comput. computer technology and development, 2009 (Vol. 308-310). |
| [23] | Kong, T. L., & Isa, N. A. M. (2017). Bi-histogram modification method for non-uniform illumination and low-contrast images. Multimedia Tools and Applications,77, 8955-8978. · doi:10.1007/s11042-017-4789-4 |
| [24] | Lai, Y.-R., Tsai, P.-C., Yao, C.-Y., & Ruan, S.-J. (2017). Improved local histogram equalization with gradient-based weighting process for edge preservation. Multimedia Tools and Applications,76, 1585-1613. · doi:10.1007/s11042-015-3147-7 |
| [25] | Li, C., & Bovik, A. C. (2010). Content-partitioned structural similarity index for image quality assessment. Signal Processing: Image Communication,25(7), 517-526. |
| [26] | Liu, B., Jin, W., Chen, Y., Liu, C., & Li, L. (2011). Contrast enhancement using non-overlapped sub-blocks and local histogram projection. IEEE Transactions on Consumer Electronics,57(2), 583-588. · doi:10.1109/TCE.2011.5955195 |
| [27] | Niu, Y., Wu, X., & Shi, G. (2016). Image enhancement by entropy maximization and quantization resolution upconversion. IEEE Transactions on Image Processing,25, 4815-4828. · Zbl 1408.94513 · doi:10.1109/TIP.2016.2598485 |
| [28] | Ooi, C. H., & Isa, N. A. M. (2010). Quadrants dynamic histogram equalization for contrast enhancement. IEEE Transactions on Consumer Electronics,56, 2552-2559. · doi:10.1109/TCE.2010.5681140 |
| [29] | Peli, E. (1990). Contrast in complex images. JOSA A,7(10), 2032-2040. · doi:10.1364/JOSAA.7.002032 |
| [30] | Priyadharsini, R., Sharmila, T. S., & Rajendran, V. (2018). A wavelet transform based contrast enhancement method for underwater acoustic images. Multidimensional Systems and Signal Processing,29(4), 1845-1859. · doi:10.1007/s11045-017-0533-5 |
| [31] | Sangee, N., Sangee, A., & Choi, H. K. (2010). Image contrast enhancement using bi-histogram equalization with neighbourhood metrics. IEEE Transactions on Consumer Electronics,56(4), 2552-2559. · doi:10.1109/TCE.2010.5681140 |
| [32] | Santhi, K., & Wahida Banu, R. S. D. (2015). Adaptive contrast enhancement using modified histogram Equalization. Optik,126, 1809-1814. · doi:10.1016/j.ijleo.2015.05.023 |
| [33] | Shakeri, M., Dezfoulian, M. H., Khotanlou, H., Barati, A. H., & Masoumi, Y. (2017). Image contrast enhancement using fuzzy clustering with adaptive cluster parameter and sub-histogram equalization. Digital Signal Processing,62, 224-237. · doi:10.1016/j.dsp.2016.10.013 |
| [34] | Shanmugavadivu, P., & Balasubramanian, K. (2014). Thresholded and optimized histogram equalization for contrast enhancement of images. Computers & Electrical Engineering,40, 757-768. · doi:10.1016/j.compeleceng.2013.06.013 |
| [35] | Sheet, D., Garud, H., Suveer, A., Mahadevappa, M., & Chatterjee, J. (2010). Brightness preserving dynamic fuzzy histogram equalization. IEEE Transactions on Consumer Electronics,56, 2475-2480. · doi:10.1109/TCE.2010.5681130 |
| [36] | Sidike, P., Sagan, V., Qumsiyeh, M., Maimaitijiang, M., Essa, A., & Asari, V. (2018). Adaptive trigonometric transformation function with image contrast and color enhancement: Application to unmanned aerial system imagery. IEEE Geoscience and Remote Sensing Letters,15(3), 404-408. · doi:10.1109/LGRS.2018.2790899 |
| [37] | Sim, K. S., Tso, C. P., & Tan, Y. Y. (2007). Recursive sub-image histogram equalization applied to gray scale images. Pattern Recognition Letters,28(10), 1209-1221. · doi:10.1016/j.patrec.2007.02.003 |
| [38] | Singh, K., & Kapoor, R. (2014a). Image enhancement using exposure based sub image histogram equalization. Pattern Recognition Letters,36, 10-14. · doi:10.1016/j.patrec.2013.08.024 |
| [39] | Singh, K., & Kapoor, R. (2014b). Image enhancement via median-mean based sub-image-clipped histogram equalization. Optik,125, 4646-4651. · doi:10.1016/j.ijleo.2014.04.093 |
| [40] | Singh, K., Kapoor, R., & Sinha, S. K. (2015). Enhancement of low exposure images via recursive histogram equalization algorithms. Optik,126, 2619-2625. · doi:10.1016/j.ijleo.2015.06.060 |
| [41] | Singh, K., Vishwakarma, D. K., Walia, G. S., & Kapoor, R. (2016). Contrast enhancement via texture region based histogram equalization. Journal of Modern Optics,63(15), 1444-1450. · doi:10.1080/09500340.2016.1154194 |
| [42] | Sundaram, M., Ramar, K., Arumugam, N., & Prabin, G. (2011). Histogram modified local contrast enhancement for mammogram images. Applied Soft Computing,11(8), 5809-5816. · doi:10.1016/j.asoc.2011.05.003 |
| [43] | Tang, J. R., & Isa, N. A. M. (2017). Bi-histogram equalization using modified histogram bins. Applied Soft Computing,55, 31-43. · doi:10.1016/j.asoc.2017.01.053 |
| [44] | Thum, C. (1984). Measurement of the entropy of an image with application to image focusing. Optica Acta: International Journal of Optics,31(2), 203-211. · doi:10.1080/713821475 |
| [45] | Wan, Y., Chen, Q., & Zhang, B. M. (1999). Image enhancement based on equal area dualistic sub-image histogram equalization method. IEEE Transactions on Consumer Electronics,45, 68-75. · doi:10.1109/30.754419 |
| [46] | Wang, X., & Chen, L. (2017). An effective histogram modification scheme for image contrast enhancement. Signal Processing: Image Communication,58, 187-198. |
| [47] | Wong, C. Y., Jiang, G., Rahman, M. A., Liu, S., Lin, S. C.-F., Kwok, N., et al. (2016). Histogram equalization and optimal profile compression based approach for colour image enhancement. Journal of Visual Communication and Image Representation,38, 802-813. · doi:10.1016/j.jvcir.2016.04.019 |
| [48] | Xiao, Y., Cao, Z., & Yuan, J. (2014). Entropic image thresholding based on GLGM histogram. Pattern Recognition Letters,40(15), 47-55. · doi:10.1016/j.patrec.2013.12.017 |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
