An Analytical Review on Image Enhancement Techniques

This study presents an organized analysis and presentation of many existing image enhancing approaches. The fundamental idea behind image enhancement is to change images informational content so that it is more suited for certain purposes. Image Enhancement is the most significant part of Digital Image Processing (DIP). It is required to mitigate noise, blur, color distortion and artifacts. There are a lot of development in every aspect of society indeed, but still, there is lack of reliable, complete clear and availability and flow of visual, text and audio information, which is sometimes life-threatening in many sensitive areas, Image enhancement technology very much depends upon the type of picture and the domain for which the image is going to be used. There is a requirement of reliable visual data in most sensitive areas such as medical, geographical, and social security, seismology and weather forecasting. Image improvement of low-light images has grown in importance as computer vision research has become more complex due to the increased demands of the field. In this paper, first the fundamental techniques of image enhancement has been reviewed for understanding purpose and then findings together with the many benefits and drawbacks of the mentioned approaches as well as the potential for further study in this field has been presented. More Emphasize on model-based techniques has been given in this article, since they are interpretable and don’t require labeled training data.

[1]  Kaidi Zhao,et al.  A New Local Enhancement Algorithm for Small Target Detection Based on Top-hat Transform , 2022, 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI).

[2]  M. K. Osman,et al.  A Comparative Study of Unsharp Masking Filters for Enhancement of Digital Breast Tomosynthesis Images , 2022, 2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE).

[3]  An Gia Vien,et al.  Histogram-Based Transformation Function Estimation for Low-Light Image Enhancement , 2022, 2022 IEEE International Conference on Image Processing (ICIP).

[4]  M. T. Rasheed,et al.  A comprehensive experiment-based review of low-light image enhancement methods and benchmarking low-light image quality assessment , 2022, Signal Process..

[5]  V. Dhandapani,et al.  Underwater Image Enhancement Using Color Constancy Via Homomorphic Filtering and Depth Estimation , 2022, 2022 International Conference on Signal and Information Processing (IConSIP).

[6]  Chong Li,et al.  Fractional-order Retinex-based low-light image enhancement fusion algorithm for energy meters , 2022, 2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC).

[7]  Chao Yang,et al.  MAGAN: Unsupervised low-light image enhancement guided by mixed-attention , 2022, Big Data Min. Anal..

[8]  Xuelong Li,et al.  Noise Removal in Embedded Image With Bit Approximation , 2022, IEEE Transactions on Knowledge and Data Engineering.

[9]  Siyu Di,et al.  Research on Low Illumination Image Processing Algorithm Based on Adaptive Parameter Homomorphic Filtering , 2022, 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML).

[10]  G. R. Reddy,et al.  Enhancement of Images Using Optimized Gamma Correction with Weighted Distribution Via Differential Evolution Algorithm , 2022, 2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT).

[11]  Rajiv Soundararajan,et al.  A low light natural image statistical model for joint contrast enhancement and denoising , 2021, Signal Process. Image Commun..

[12]  Buyut Khoirul Umri,et al.  Comparative Analysis of CLAHE and AHE on Application of CNN Algorithm in the Detection of Covid-19 Patients , 2021, 2021 4th International Conference on Information and Communications Technology (ICOIACT).

[13]  Jiankai Zuo,et al.  A Novel Lightweight Infrared and Visible Image Fusion Algorithm , 2021, 2021 International Conference of Optical Imaging and Measurement (ICOIM).

[14]  Hayde Peregrina-Barreto,et al.  Visible-NIR Image Fusion Based on Top-Hat Transform , 2021, IEEE Transactions on Image Processing.

[15]  Jacques Facon,et al.  Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology , 2021, Sensors.

[16]  Yide Ma,et al.  A Comprehensive Overview of Image Enhancement Techniques , 2021, Archives of Computational Methods in Engineering.

[17]  D. Koundal,et al.  Image Fusion Techniques: A Survey , 2021, Archives of Computational Methods in Engineering.

[18]  Neeru Jindal,et al.  Fractional derivative based Unsharp masking approach for enhancement of digital images , 2020, Multimedia Tools and Applications.

[19]  Yu Guo,et al.  Low-Light Image Enhancement With Regularized Illumination Optimization and Deep Noise Suppression , 2020, IEEE Access.

[20]  Canran Xu,et al.  FPGA-Based Low-Visibility Enhancement Accelerator for Video Sequence by Adaptive Histogram Equalization With Dynamic Clip-Threshold , 2020, IEEE Transactions on Circuits and Systems I: Regular Papers.

[21]  O. P. Acharya,et al.  A Comprehensive Survey on Image Contrast Enhancement Techniques in Spatial Domain , 2020, Sensing and Imaging.

[22]  Zhiqin Zhu,et al.  Image Dehazing by an Artificial Image Fusion Method Based on Adaptive Structure Decomposition , 2020, IEEE Sensors Journal.

[23]  Zairui Gao,et al.  An Experiment-Based Review of Low-Light Image Enhancement Methods , 2020, IEEE Access.

[24]  Xingchen Zhang,et al.  Multi-focus Image Fusion: A Benchmark , 2020, ArXiv.

[25]  Kunio Kashino,et al.  Reflectance-Guided, Contrast-Accumulated Histogram Equalization , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[26]  Singara Singh Kasana,et al.  Improved color attenuation prior based image de-fogging technique , 2020, Multimedia Tools and Applications.

[27]  Ping Xia,et al.  Low SNR Sonar Image Restoration Based on Mixed Probability Statistical Model in Wavelet Domain , 2019, 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom).

[28]  Shuaiqi Liu,et al.  A new focus evaluation operator based on max–min filter and its application in high quality multi-focus image fusion , 2019, Multidimensional Systems and Signal Processing.

[29]  Kulbir Singh,et al.  An improved robust image-adaptive watermarking with two watermarks using statistical decoder , 2019, Multimedia Tools and Applications.

[30]  Minsong Wei,et al.  Multimorphological top-hat-based multiscale target classification algorithm for real-time image processing. , 2019, Applied optics.

[31]  Weimin Tan,et al.  RDGAN: Retinex Decomposition Based Adversarial Learning for Low-Light Enhancement , 2019, 2019 IEEE International Conference on Multimedia and Expo (ICME).

[32]  A B Shahriman,et al.  Image Enhancement Based on Discrete Cosine Transforms (DCT) and Discrete Wavelet Transform (DWT): A Review , 2019, IOP Conference Series: Materials Science and Engineering.

[33]  Ling Shao,et al.  STAR: A Structure and Texture Aware Retinex Model , 2019, IEEE Transactions on Image Processing.

[34]  Diego P. Pinto-Roa,et al.  Image enhancement with preservation of brightness and details using multiscale top-hat transform , 2019, 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA).

[35]  Mohammad Shorif Uddin,et al.  Image Quality Assessment through FSIM, SSIM, MSE and PSNR—A Comparative Study , 2019, Journal of Computer and Communications.

[36]  Horacio Andrés Legal-Ayala,et al.  Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform , 2019, Entropy.

[37]  Jie Zhao,et al.  Multi-Focus Image Fusion Based on Adaptive Dual-Channel Spiking Cortical Model in Non-Subsampled Shearlet Domain , 2019, IEEE Access.

[38]  Di Wang,et al.  A Phase Congruency and Local Laplacian Energy Based Multi-Modality Medical Image Fusion Method in NSCT Domain , 2019, IEEE Access.

[39]  David Zhang,et al.  A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[40]  N Suvitha.,et al.  Image Fusion Techniques-A Survey , 2018, International Journal for Research in Applied Science and Engineering Technology.

[41]  Xiaoyan Sun,et al.  Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model , 2018, IEEE Transactions on Image Processing.

[42]  Savita Gupta,et al.  Computer aided thyroid nodule detection system using medical ultrasound images , 2018, Biomed. Signal Process. Control..

[43]  Chien-Cheng Tseng,et al.  A weak-illumation image enhancement method uisng homomorphic filter and image fusion , 2017, 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE).

[44]  Jose Luis Vazquez Noguera,et al.  Top-Hat Transform for Enhancement of Aerial Thermal Images , 2017, 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).

[45]  Dacheng Tao,et al.  A Joint Intrinsic-Extrinsic Prior Model for Retinex , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[46]  Delu Zeng,et al.  A fusion-based enhancing method for weakly illuminated images , 2016, Signal Process..

[47]  Xiao-Ping Zhang,et al.  A fusion-based method for single backlit image enhancement , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[48]  Md. Shahnawaz Shaikh,et al.  Analysis of Digital Image Filters in Frequency Domain , 2016 .

[49]  Mayank Tiwari,et al.  Brightness preserving contrast enhancement of medical images using adaptive gamma correction and homomorphic filtering , 2016, 2016 IEEE Students' Conference on Electrical, Electronics and Computer Science (SCEECS).

[50]  Chul Lee,et al.  Contrast Enhancement Based on Layered Difference Representation of 2D Histograms , 2013, IEEE Transactions on Image Processing.

[51]  Shih-Chia Huang,et al.  Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution , 2013, IEEE Transactions on Image Processing.

[52]  Stephen Lin,et al.  A Closed-Form Solution to Retinex with Nonlocal Texture Constraints , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[53]  Xiangzhi Bai,et al.  Analysis of top-hat selection transformation and some modified top-hat transformations , 2012 .

[54]  K. S. Sim,et al.  Image enhancement using background brightness preserving histogram equalisation , 2012 .

[55]  Oge Marques,et al.  Morphological Image Processing , 2011 .

[56]  A. Sreenivasa Murthy,et al.  A comparison between different colour image contrast enhancement algorithms , 2011, 2011 International Conference on Emerging Trends in Electrical and Computer Technology.

[57]  Xiangzhi Bai,et al.  Enhancement of dim small target through modified top-hat transformation under the condition of heavy clutter , 2010, Signal Process..

[58]  Abd. Rahman Ramli,et al.  Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation , 2003, IEEE Trans. Consumer Electron..

[59]  Abd. Rahman Ramli,et al.  Minimum mean brightness error bi-histogram equalization in contrast enhancement , 2003, IEEE Trans. Consumer Electron..

[60]  Lee-Sup Kim,et al.  An advanced contrast enhancement using partially overlapped sub-block histogram equalization , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).

[61]  Giovanni Ramponi,et al.  Image enhancement via adaptive unsharp masking , 2000, IEEE Trans. Image Process..

[62]  Zia-ur Rahman,et al.  A multiscale retinex for bridging the gap between color images and the human observation of scenes , 1997, IEEE Trans. Image Process..

[63]  Sanjit K. Mitra,et al.  Nonlinear unsharp masking methods for image contrast enhancement , 1996, J. Electronic Imaging.

[64]  Sanjit K. Mitra,et al.  Quadratic filters for image contrast enhancement , 1994, Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers.

[65]  Futuristic Trends in Networks and Computing Technologies: Select Proceedings of Fourth International Conference on FTNCT 2021 , 2022, Lecture Notes in Electrical Engineering.

[66]  Samer Hameed Majeed,et al.  Adaptive Entropy Index Histogram Equalization for Poor Contrast Images , 2021, IEEE Access.

[67]  Faouzi Alaya Cheikh,et al.  Cross-Modality Guided Contrast Enhancement for Improved Liver Tumor Image Segmentation , 2021, IEEE Access.

[68]  Tianhe Yu,et al.  Image Enhancement Algorithm Based on Image Spatial Domain Segmentation , 2021, Comput. Informatics.

[69]  Jingwen Yan,et al.  Low-Light Image Enhancement via Pair of Complementary Gamma Functions by Fusion , 2020, IEEE Access.

[70]  Sandeep Kumar,et al.  Image Enhancement Using Exposure and Standard Deviation-Based Sub-image Histogram Equalization for Night-time Images , 2020 .

[71]  K. Suganthi,et al.  Image Contrast Enhancement by Homomorphic Filtering based Parametric Fuzzy Transform , 2019, Procedia Computer Science.

[72]  Li Li,et al.  Contrast Enhancement Algorithm for Outdoor Infrared Images Based on Local Gradient-Grayscale Statistical Feature , 2018, IEEE Access.

[73]  Ngaiming Kwok,et al.  Intensity and edge based adaptive unsharp masking filter for color image enhancement , 2016 .

[74]  Pooja Gupta,et al.  Colour image Enhancement using Background Brightness Preserving Histogram Equalization , 2016 .

[75]  Chao Wang,et al.  Brightness preserving histogram equalization with maximum entropy: a variational perspective , 2005, IEEE Transactions on Consumer Electronics.

[76]  Martin J. Wainwright,et al.  Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..